The following values were not passed to `accelerate launch` and had defaults used instead:
	`--num_processes` was set to a value of `4`
		More than one GPU was found, enabling multi-GPU training.
		If this was unintended please pass in `--num_processes=1`.
	`--num_machines` was set to a value of `1`
	`--mixed_precision` was set to a value of `'no'`
	`--dynamo_backend` was set to a value of `'no'`
To avoid this warning pass in values for each of the problematic parameters or run `accelerate config`.
Params using prompt template alpaca:
base_model: baichuan-inc/Baichuan2-7B-Base
data_path: ../../data/belle_dolphine/p13.jsonl
output_dir: ../out/lora/p13
batch_size: 32
micro_batch_size: 2
num_epochs: 1
learning_rate: 0.0004
cutoff_len: 4096
val_set_size: 0
lr_scheduler: cosine
warmup_steps: 100
lora_r: 16
lora_alpha: 16
lora_dropout: 0.05
lora_target_modules: ['gate_proj', 'down_proj', 'up_proj']
train_on_inputs: False
add_eos_token: False
group_by_length: False
wandb_project: lora-moe
wandb_run_name: belle_dolphine-p13
wandb_watch: 
wandb_log_model: 
resume_from_checkpoint: False

gradient_accumulation_steps:  4
gradient_accumulation_steps:  4
gradient_accumulation_steps:  4
gradient_accumulation_steps:  4

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pre-trained model's BOS EOS and PAD token id: 1 2 0  => It should be 1 2 None
pre-trained model's BOS EOS and PAD token id: 1 2 0  => It should be 1 2 None

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pre-trained model's BOS EOS and PAD token id: 1 2 0  => It should be 1 2 None
pre-trained model's BOS EOS and PAD token id: 1 2 0  => It should be 1 2 None
trainable params: 23,199,744 || all params: 7,529,172,992 || trainable%: 0.30813137146205183trainable params: 23,199,744 || all params: 7,529,172,992 || trainable%: 0.30813137146205183


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Map:  99%|█████████▉| 109482/110379 [02:52<00:01, 664.85 examples/s]Detected kernel version 5.4.0, which is below the recommended minimum of 5.5.0; this can cause the process to hang. It is recommended to upgrade the kernel to the minimum version or higher.

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/home/aiops/duanky/miniconda3/envs/lora/lib/python3.11/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/home/aiops/duanky/miniconda3/envs/lora/lib/python3.11/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/home/aiops/duanky/miniconda3/envs/lora/lib/python3.11/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
wandb: Currently logged in as: k-duan (nus_keyu). Use `wandb login --relogin` to force relogin
wandb: Tracking run with wandb version 0.16.1
wandb: Run data is saved locally in /home/aiops/duanky/lora-moe/experiments/launch_scripts/wandb/run-20231229_120011-rpu8pnl2
wandb: Run `wandb offline` to turn off syncing.
wandb: Syncing run belle_dolphine-p13
wandb: ⭐️ View project at https://wandb.ai/nus_keyu/lora-moe
wandb: 🚀 View run at https://wandb.ai/nus_keyu/lora-moe/runs/rpu8pnl2

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  warnings.warn(

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{'loss': 1.5658, 'learning_rate': 0.000244, 'epoch': 0.02}

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{'loss': 1.3968, 'learning_rate': 0.000248, 'epoch': 0.02}

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{'loss': 1.4089, 'learning_rate': 0.000252, 'epoch': 0.02}

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{'loss': 1.3224, 'learning_rate': 0.00025600000000000004, 'epoch': 0.02}

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{'loss': 1.5052, 'learning_rate': 0.00026000000000000003, 'epoch': 0.02}

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{'loss': 1.4618, 'learning_rate': 0.000264, 'epoch': 0.02}

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{'loss': 1.405, 'learning_rate': 0.000268, 'epoch': 0.02}

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{'loss': 1.3175, 'learning_rate': 0.00027200000000000005, 'epoch': 0.02}

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{'loss': 1.2401, 'learning_rate': 0.000276, 'epoch': 0.02}

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{'loss': 1.3094, 'learning_rate': 0.00028, 'epoch': 0.02}

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{'loss': 1.2717, 'learning_rate': 0.000284, 'epoch': 0.02}

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{'loss': 1.2567, 'learning_rate': 0.000288, 'epoch': 0.02}

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{'loss': 1.4094, 'learning_rate': 0.000292, 'epoch': 0.02}

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{'loss': 1.3668, 'learning_rate': 0.000296, 'epoch': 0.02}

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{'loss': 1.2809, 'learning_rate': 0.00030000000000000003, 'epoch': 0.02}

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{'loss': 1.6195, 'learning_rate': 0.000304, 'epoch': 0.02}

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{'loss': 1.5164, 'learning_rate': 0.000308, 'epoch': 0.02}

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{'loss': 1.3275, 'learning_rate': 0.00031200000000000005, 'epoch': 0.02}

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{'loss': 1.3314, 'learning_rate': 0.00031600000000000004, 'epoch': 0.02}

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{'loss': 1.4825, 'learning_rate': 0.00032, 'epoch': 0.02}

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{'loss': 1.4019, 'learning_rate': 0.000324, 'epoch': 0.02}

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{'loss': 1.3452, 'learning_rate': 0.000328, 'epoch': 0.02}

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{'loss': 1.279, 'learning_rate': 0.000332, 'epoch': 0.02}

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{'loss': 1.4439, 'learning_rate': 0.000336, 'epoch': 0.02}

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{'loss': 1.3839, 'learning_rate': 0.00034, 'epoch': 0.02}

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{'loss': 1.2913, 'learning_rate': 0.000344, 'epoch': 0.02}

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{'loss': 1.3672, 'learning_rate': 0.000348, 'epoch': 0.03}

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{'loss': 1.4193, 'learning_rate': 0.00035200000000000005, 'epoch': 0.03}

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{'loss': 1.4455, 'learning_rate': 0.00035600000000000003, 'epoch': 0.03}

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{'loss': 1.2722, 'learning_rate': 0.00036, 'epoch': 0.03}

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{'loss': 1.5172, 'learning_rate': 0.000364, 'epoch': 0.03}

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{'loss': 1.4723, 'learning_rate': 0.00036800000000000005, 'epoch': 0.03}

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{'loss': 1.2708, 'learning_rate': 0.00037200000000000004, 'epoch': 0.03}

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{'loss': 1.4163, 'learning_rate': 0.000376, 'epoch': 0.03}

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{'loss': 1.4054, 'learning_rate': 0.00038, 'epoch': 0.03}

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{'loss': 1.3794, 'learning_rate': 0.000384, 'epoch': 0.03}

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{'loss': 1.3473, 'learning_rate': 0.000388, 'epoch': 0.03}

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{'loss': 1.5271, 'learning_rate': 0.000392, 'epoch': 0.03}

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{'loss': 1.4365, 'learning_rate': 0.00039600000000000003, 'epoch': 0.03}

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{'loss': 1.5053, 'learning_rate': 0.0004, 'epoch': 0.03}

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{'loss': 1.3237, 'learning_rate': 0.0003999999120026855, 'epoch': 0.03}

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{'loss': 1.5015, 'learning_rate': 0.00039999964801081954, 'epoch': 0.03}

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{'loss': 1.2449, 'learning_rate': 0.0003999992080246343, 'epoch': 0.03}

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{'loss': 1.4435, 'learning_rate': 0.0003999985920445171, 'epoch': 0.03}

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{'loss': 1.4326, 'learning_rate': 0.0003999978000710098, 'epoch': 0.03}

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{'loss': 1.4118, 'learning_rate': 0.0003999968321048095, 'epoch': 0.03}

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{'loss': 1.4152, 'learning_rate': 0.0003999956881467678, 'epoch': 0.03}

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{'loss': 1.3995, 'learning_rate': 0.00039999436819789153, 'epoch': 0.03}

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{'loss': 1.3273, 'learning_rate': 0.0003999928722593421, 'epoch': 0.03}

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{'loss': 1.2412, 'learning_rate': 0.000399991200332436, 'epoch': 0.03}

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{'loss': 1.404, 'learning_rate': 0.0003999893524186444, 'epoch': 0.03}

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{'loss': 1.4241, 'learning_rate': 0.0003999873285195934, 'epoch': 0.03}

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{'loss': 1.3263, 'learning_rate': 0.000399985128637064, 'epoch': 0.03}

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{'loss': 1.4066, 'learning_rate': 0.000399982752772992, 'epoch': 0.03}

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{'loss': 1.4737, 'learning_rate': 0.00039998020092946824, 'epoch': 0.03}

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{'loss': 1.3736, 'learning_rate': 0.0003999774731087381, 'epoch': 0.03}

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{'loss': 1.3962, 'learning_rate': 0.0003999745693132021, 'epoch': 0.03}

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{'loss': 1.4497, 'learning_rate': 0.00039997148954541543, 'epoch': 0.03}

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{'loss': 1.3684, 'learning_rate': 0.00039996823380808824, 'epoch': 0.03}

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{'loss': 1.396, 'learning_rate': 0.0003999648021040855, 'epoch': 0.03}

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{'loss': 1.4098, 'learning_rate': 0.000399961194436427, 'epoch': 0.04}

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{'loss': 1.4442, 'learning_rate': 0.00039995741080828734, 'epoch': 0.04}

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{'loss': 1.3268, 'learning_rate': 0.0003999534512229961, 'epoch': 0.04}

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{'loss': 1.4533, 'learning_rate': 0.00039994931568403764, 'epoch': 0.04}

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{'loss': 1.2902, 'learning_rate': 0.000399945004195051, 'epoch': 0.04}

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{'loss': 1.3231, 'learning_rate': 0.0003999405167598303, 'epoch': 0.04}

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{'loss': 1.4404, 'learning_rate': 0.0003999358533823242, 'epoch': 0.04}

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{'loss': 1.5074, 'learning_rate': 0.0003999310140666365, 'epoch': 0.04}

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{'loss': 1.5619, 'learning_rate': 0.00039992599881702554, 'epoch': 0.04}

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{'loss': 1.4426, 'learning_rate': 0.00039992080763790475, 'epoch': 0.04}

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{'loss': 1.2351, 'learning_rate': 0.00039991544053384213, 'epoch': 0.04}

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{'loss': 1.3252, 'learning_rate': 0.00039990989750956064, 'epoch': 0.04}

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{'loss': 1.4116, 'learning_rate': 0.00039990417856993794, 'epoch': 0.04}

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{'loss': 1.3452, 'learning_rate': 0.00039989828372000657, 'epoch': 0.04}

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{'loss': 1.3856, 'learning_rate': 0.0003998922129649538, 'epoch': 0.04}

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{'loss': 1.3277, 'learning_rate': 0.0003998859663101218, 'epoch': 0.04}

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{'loss': 1.4707, 'learning_rate': 0.0003998795437610074, 'epoch': 0.04}

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{'loss': 1.4154, 'learning_rate': 0.00039987294532326233, 'epoch': 0.04}

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{'loss': 1.4648, 'learning_rate': 0.000399866171002693, 'epoch': 0.04}

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{'loss': 1.3241, 'learning_rate': 0.00039985922080526065, 'epoch': 0.04}

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{'loss': 1.3787, 'learning_rate': 0.0003998520947370812, 'epoch': 0.04}

  4%|▍         | 141/3449 [06:41<2:25:42,  2.64s/it]
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{'loss': 1.1477, 'learning_rate': 0.0003998447928044255, 'epoch': 0.04}

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{'loss': 1.4423, 'learning_rate': 0.000399837315013719, 'epoch': 0.04}

  4%|▍         | 143/3449 [06:46<2:26:05,  2.65s/it]
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{'loss': 1.4003, 'learning_rate': 0.00039982966137154193, 'epoch': 0.04}

  4%|▍         | 144/3449 [06:49<2:29:01,  2.71s/it]
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{'loss': 1.3892, 'learning_rate': 0.0003998218318846293, 'epoch': 0.04}

  4%|▍         | 145/3449 [06:52<2:23:52,  2.61s/it]
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{'loss': 1.4127, 'learning_rate': 0.00039981382655987095, 'epoch': 0.04}

  4%|▍         | 146/3449 [06:55<2:40:01,  2.91s/it]
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{'loss': 1.4172, 'learning_rate': 0.00039980564540431125, 'epoch': 0.04}

  4%|▍         | 147/3449 [06:58<2:37:40,  2.86s/it]
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{'loss': 1.3198, 'learning_rate': 0.00039979728842514935, 'epoch': 0.04}

  4%|▍         | 148/3449 [07:01<2:40:26,  2.92s/it]
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{'loss': 1.3332, 'learning_rate': 0.00039978875562973927, 'epoch': 0.04}

  4%|▍         | 149/3449 [07:04<2:34:55,  2.82s/it]
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{'loss': 1.4563, 'learning_rate': 0.00039978004702558966, 'epoch': 0.04}

  4%|▍         | 150/3449 [07:06<2:31:30,  2.76s/it]
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{'loss': 1.4628, 'learning_rate': 0.0003997711626203637, 'epoch': 0.04}

  4%|▍         | 151/3449 [07:09<2:31:30,  2.76s/it]
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{'loss': 1.358, 'learning_rate': 0.00039976210242187964, 'epoch': 0.04}

  4%|▍         | 152/3449 [07:12<2:32:16,  2.77s/it]
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{'loss': 1.2227, 'learning_rate': 0.00039975286643811, 'epoch': 0.04}

  4%|▍         | 153/3449 [07:15<2:33:10,  2.79s/it]
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{'loss': 1.4093, 'learning_rate': 0.0003997434546771824, 'epoch': 0.04}

  4%|▍         | 154/3449 [07:17<2:26:37,  2.67s/it]
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{'loss': 1.3938, 'learning_rate': 0.0003997338671473787, 'epoch': 0.04}

  4%|▍         | 155/3449 [07:20<2:24:31,  2.63s/it]
  5%|▍         | 156/3449 [07:22<2:23:14,  2.61s/it]
                                                    
{'loss': 1.2654, 'learning_rate': 0.0003997241038571359, 'epoch': 0.05}

  5%|▍         | 156/3449 [07:22<2:23:14,  2.61s/it]
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{'loss': 1.3301, 'learning_rate': 0.00039971416481504536, 'epoch': 0.05}

  5%|▍         | 157/3449 [07:25<2:23:58,  2.62s/it]
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{'loss': 1.4287, 'learning_rate': 0.0003997040500298531, 'epoch': 0.05}

  5%|▍         | 158/3449 [07:27<2:22:14,  2.59s/it]
  5%|▍         | 159/3449 [07:30<2:24:50,  2.64s/it]
                                                    
{'loss': 1.5021, 'learning_rate': 0.00039969375951045985, 'epoch': 0.05}

  5%|▍         | 159/3449 [07:30<2:24:50,  2.64s/it]
  5%|▍         | 160/3449 [07:33<2:29:56,  2.74s/it]
                                                    
{'loss': 1.3404, 'learning_rate': 0.00039968329326592117, 'epoch': 0.05}

  5%|▍         | 160/3449 [07:33<2:29:56,  2.74s/it]
  5%|▍         | 161/3449 [07:36<2:26:46,  2.68s/it]
                                                    
{'loss': 1.3392, 'learning_rate': 0.0003996726513054469, 'epoch': 0.05}

  5%|▍         | 161/3449 [07:36<2:26:46,  2.68s/it]
  5%|▍         | 162/3449 [07:38<2:25:55,  2.66s/it]
                                                    
{'loss': 1.4043, 'learning_rate': 0.0003996618336384017, 'epoch': 0.05}

  5%|▍         | 162/3449 [07:38<2:25:55,  2.66s/it]
  5%|▍         | 163/3449 [07:41<2:22:16,  2.60s/it]
                                                    
{'loss': 1.2441, 'learning_rate': 0.00039965084027430487, 'epoch': 0.05}

  5%|▍         | 163/3449 [07:41<2:22:16,  2.60s/it]
  5%|▍         | 164/3449 [07:43<2:19:01,  2.54s/it]
                                                    
{'loss': 1.442, 'learning_rate': 0.00039963967122283033, 'epoch': 0.05}

  5%|▍         | 164/3449 [07:43<2:19:01,  2.54s/it]
  5%|▍         | 165/3449 [07:46<2:27:03,  2.69s/it]
                                                    
{'loss': 1.3297, 'learning_rate': 0.00039962832649380635, 'epoch': 0.05}

  5%|▍         | 165/3449 [07:46<2:27:03,  2.69s/it]
  5%|▍         | 166/3449 [07:49<2:25:05,  2.65s/it]
                                                    
{'loss': 1.3974, 'learning_rate': 0.00039961680609721626, 'epoch': 0.05}

  5%|▍         | 166/3449 [07:49<2:25:05,  2.65s/it]
  5%|▍         | 167/3449 [07:51<2:22:18,  2.60s/it]
                                                    
{'loss': 1.4026, 'learning_rate': 0.00039960511004319746, 'epoch': 0.05}

  5%|▍         | 167/3449 [07:51<2:22:18,  2.60s/it]
  5%|▍         | 168/3449 [07:54<2:27:41,  2.70s/it]
                                                    
{'loss': 1.4038, 'learning_rate': 0.0003995932383420423, 'epoch': 0.05}

  5%|▍         | 168/3449 [07:54<2:27:41,  2.70s/it]
  5%|▍         | 169/3449 [07:57<2:31:11,  2.77s/it]
                                                    
{'loss': 1.2948, 'learning_rate': 0.0003995811910041975, 'epoch': 0.05}

  5%|▍         | 169/3449 [07:57<2:31:11,  2.77s/it]
  5%|▍         | 170/3449 [08:00<2:37:19,  2.88s/it]
                                                    
{'loss': 1.504, 'learning_rate': 0.0003995689680402644, 'epoch': 0.05}

  5%|▍         | 170/3449 [08:00<2:37:19,  2.88s/it]
  5%|▍         | 171/3449 [08:03<2:37:41,  2.89s/it]
                                                    
{'loss': 1.2047, 'learning_rate': 0.00039955656946099894, 'epoch': 0.05}

  5%|▍         | 171/3449 [08:03<2:37:41,  2.89s/it]
  5%|▍         | 172/3449 [08:06<2:31:44,  2.78s/it]
                                                    
{'loss': 1.328, 'learning_rate': 0.0003995439952773114, 'epoch': 0.05}

  5%|▍         | 172/3449 [08:06<2:31:44,  2.78s/it]
  5%|▌         | 173/3449 [08:09<2:40:35,  2.94s/it]
                                                    
{'loss': 1.3518, 'learning_rate': 0.0003995312455002669, 'epoch': 0.05}

  5%|▌         | 173/3449 [08:09<2:40:35,  2.94s/it]
  5%|▌         | 174/3449 [08:11<2:31:47,  2.78s/it]
                                                    
{'loss': 1.4515, 'learning_rate': 0.0003995183201410848, 'epoch': 0.05}

  5%|▌         | 174/3449 [08:11<2:31:47,  2.78s/it]
  5%|▌         | 175/3449 [08:14<2:30:49,  2.76s/it]
                                                    
{'loss': 1.3857, 'learning_rate': 0.000399505219211139, 'epoch': 0.05}

  5%|▌         | 175/3449 [08:14<2:30:49,  2.76s/it]
  5%|▌         | 176/3449 [08:17<2:33:26,  2.81s/it]
                                                    
{'loss': 1.4068, 'learning_rate': 0.0003994919427219581, 'epoch': 0.05}

  5%|▌         | 176/3449 [08:17<2:33:26,  2.81s/it]
  5%|▌         | 177/3449 [08:20<2:36:30,  2.87s/it]
                                                    
{'loss': 1.2225, 'learning_rate': 0.000399478490685225, 'epoch': 0.05}

  5%|▌         | 177/3449 [08:20<2:36:30,  2.87s/it]
  5%|▌         | 178/3449 [08:23<2:36:33,  2.87s/it]
                                                    
{'loss': 1.3794, 'learning_rate': 0.0003994648631127772, 'epoch': 0.05}

  5%|▌         | 178/3449 [08:23<2:36:33,  2.87s/it]
  5%|▌         | 179/3449 [08:25<2:30:48,  2.77s/it]
                                                    
{'loss': 1.4642, 'learning_rate': 0.0003994510600166065, 'epoch': 0.05}

  5%|▌         | 179/3449 [08:25<2:30:48,  2.77s/it]
  5%|▌         | 180/3449 [08:28<2:26:31,  2.69s/it]
                                                    
{'loss': 1.2692, 'learning_rate': 0.00039943708140885925, 'epoch': 0.05}

  5%|▌         | 180/3449 [08:28<2:26:31,  2.69s/it]
  5%|▌         | 181/3449 [08:31<2:31:22,  2.78s/it]
                                                    
{'loss': 1.3233, 'learning_rate': 0.00039942292730183625, 'epoch': 0.05}

  5%|▌         | 181/3449 [08:31<2:31:22,  2.78s/it]
  5%|▌         | 182/3449 [08:34<2:29:58,  2.75s/it]
                                                    
{'loss': 1.2888, 'learning_rate': 0.0003994085977079928, 'epoch': 0.05}

  5%|▌         | 182/3449 [08:34<2:29:58,  2.75s/it]
  5%|▌         | 183/3449 [08:38<2:59:28,  3.30s/it]
                                                    
{'loss': 1.4167, 'learning_rate': 0.00039939409263993854, 'epoch': 0.05}

  5%|▌         | 183/3449 [08:38<2:59:28,  3.30s/it]
  5%|▌         | 184/3449 [08:41<2:47:10,  3.07s/it]
                                                    
{'loss': 1.3193, 'learning_rate': 0.0003993794121104375, 'epoch': 0.05}

  5%|▌         | 184/3449 [08:41<2:47:10,  3.07s/it]
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{'loss': 1.4016, 'learning_rate': 0.0003993645561324082, 'epoch': 0.05}

  5%|▌         | 185/3449 [08:44<2:45:56,  3.05s/it]
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{'loss': 1.3544, 'learning_rate': 0.0003993495247189235, 'epoch': 0.05}

  5%|▌         | 186/3449 [08:46<2:34:38,  2.84s/it]
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{'loss': 1.4277, 'learning_rate': 0.0003993343178832106, 'epoch': 0.05}

  5%|▌         | 187/3449 [08:49<2:32:17,  2.80s/it]
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{'loss': 1.4128, 'learning_rate': 0.00039931893563865115, 'epoch': 0.05}

  5%|▌         | 188/3449 [08:51<2:31:15,  2.78s/it]
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{'loss': 1.3224, 'learning_rate': 0.00039930337799878103, 'epoch': 0.05}

  5%|▌         | 189/3449 [08:54<2:26:05,  2.69s/it]
  6%|▌         | 190/3449 [08:56<2:21:31,  2.61s/it]
                                                    
{'loss': 1.4007, 'learning_rate': 0.0003992876449772907, 'epoch': 0.06}

  6%|▌         | 190/3449 [08:56<2:21:31,  2.61s/it]
  6%|▌         | 191/3449 [09:00<2:32:00,  2.80s/it]
                                                    
{'loss': 1.2749, 'learning_rate': 0.0003992717365880246, 'epoch': 0.06}

  6%|▌         | 191/3449 [09:00<2:32:00,  2.80s/it]
  6%|▌         | 192/3449 [09:03<2:33:20,  2.82s/it]
                                                    
{'loss': 1.3118, 'learning_rate': 0.00039925565284498185, 'epoch': 0.06}

  6%|▌         | 192/3449 [09:03<2:33:20,  2.82s/it]
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{'loss': 1.2867, 'learning_rate': 0.00039923939376231563, 'epoch': 0.06}

  6%|▌         | 193/3449 [09:06<2:44:38,  3.03s/it]
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{'loss': 1.3441, 'learning_rate': 0.00039922295935433346, 'epoch': 0.06}

  6%|▌         | 194/3449 [09:09<2:36:13,  2.88s/it]
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{'loss': 1.3888, 'learning_rate': 0.0003992063496354973, 'epoch': 0.06}

  6%|▌         | 195/3449 [09:11<2:35:14,  2.86s/it]
  6%|▌         | 196/3449 [09:14<2:30:26,  2.77s/it]
                                                    
{'loss': 1.405, 'learning_rate': 0.0003991895646204232, 'epoch': 0.06}

  6%|▌         | 196/3449 [09:14<2:30:26,  2.77s/it]
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{'loss': 1.4234, 'learning_rate': 0.00039917260432388146, 'epoch': 0.06}

  6%|▌         | 197/3449 [09:17<2:29:40,  2.76s/it]
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{'loss': 1.4004, 'learning_rate': 0.0003991554687607968, 'epoch': 0.06}

  6%|▌         | 198/3449 [09:19<2:22:16,  2.63s/it]
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{'loss': 1.4156, 'learning_rate': 0.000399138157946248, 'epoch': 0.06}

  6%|▌         | 199/3449 [09:21<2:16:16,  2.52s/it]
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{'loss': 1.4495, 'learning_rate': 0.000399120671895468, 'epoch': 0.06}

  6%|▌         | 200/3449 [09:24<2:24:52,  2.68s/it]
  6%|▌         | 201/3449 [09:27<2:27:17,  2.72s/it]
                                                    
{'loss': 1.4346, 'learning_rate': 0.0003991030106238442, 'epoch': 0.06}

  6%|▌         | 201/3449 [09:27<2:27:17,  2.72s/it]
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{'loss': 1.2202, 'learning_rate': 0.000399085174146918, 'epoch': 0.06}

  6%|▌         | 202/3449 [09:29<2:21:29,  2.61s/it]
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{'loss': 1.473, 'learning_rate': 0.00039906716248038507, 'epoch': 0.06}

  6%|▌         | 203/3449 [09:32<2:22:08,  2.63s/it]
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{'loss': 1.3089, 'learning_rate': 0.0003990489756400951, 'epoch': 0.06}

  6%|▌         | 204/3449 [09:35<2:30:54,  2.79s/it]
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{'loss': 1.3049, 'learning_rate': 0.0003990306136420521, 'epoch': 0.06}

  6%|▌         | 205/3449 [09:39<2:42:31,  3.01s/it]
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{'loss': 1.3764, 'learning_rate': 0.0003990120765024141, 'epoch': 0.06}

  6%|▌         | 206/3449 [09:42<2:44:51,  3.05s/it]
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{'loss': 1.272, 'learning_rate': 0.0003989933642374933, 'epoch': 0.06}

  6%|▌         | 207/3449 [09:45<2:41:27,  2.99s/it]
  6%|▌         | 208/3449 [09:48<2:37:15,  2.91s/it]
                                                    
{'loss': 1.3248, 'learning_rate': 0.0003989744768637559, 'epoch': 0.06}

  6%|▌         | 208/3449 [09:48<2:37:15,  2.91s/it]
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{'loss': 1.3713, 'learning_rate': 0.0003989554143978224, 'epoch': 0.06}

  6%|▌         | 209/3449 [09:50<2:33:02,  2.83s/it]
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{'loss': 1.5846, 'learning_rate': 0.0003989361768564673, 'epoch': 0.06}

  6%|▌         | 210/3449 [09:53<2:35:25,  2.88s/it]
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{'loss': 1.3624, 'learning_rate': 0.000398916764256619, 'epoch': 0.06}

  6%|▌         | 211/3449 [09:56<2:32:19,  2.82s/it]
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{'loss': 1.3555, 'learning_rate': 0.00039889717661536003, 'epoch': 0.06}

  6%|▌         | 212/3449 [09:59<2:37:22,  2.92s/it]
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{'loss': 1.2427, 'learning_rate': 0.00039887741394992713, 'epoch': 0.06}

  6%|▌         | 213/3449 [10:02<2:35:34,  2.88s/it]
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{'loss': 1.4018, 'learning_rate': 0.0003988574762777108, 'epoch': 0.06}

  6%|▌         | 214/3449 [10:04<2:25:30,  2.70s/it]
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{'loss': 1.3019, 'learning_rate': 0.0003988373636162558, 'epoch': 0.06}

  6%|▌         | 215/3449 [10:07<2:24:38,  2.68s/it]
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{'loss': 1.3403, 'learning_rate': 0.0003988170759832605, 'epoch': 0.06}

  6%|▋         | 216/3449 [10:09<2:20:59,  2.62s/it]
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{'loss': 1.3435, 'learning_rate': 0.00039879661339657776, 'epoch': 0.06}

  6%|▋         | 217/3449 [10:12<2:23:41,  2.67s/it]
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{'loss': 1.4053, 'learning_rate': 0.0003987759758742138, 'epoch': 0.06}

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{'loss': 1.4096, 'learning_rate': 0.00039875516343432937, 'epoch': 0.06}

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{'loss': 1.4866, 'learning_rate': 0.00039873417609523863, 'epoch': 0.06}

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{'loss': 1.4622, 'learning_rate': 0.00039871301387541, 'epoch': 0.06}

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{'loss': 1.3574, 'learning_rate': 0.00039869167679346573, 'epoch': 0.06}

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{'loss': 1.4224, 'learning_rate': 0.0003986701648681817, 'epoch': 0.06}

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{'loss': 1.3927, 'learning_rate': 0.000398648478118488, 'epoch': 0.06}

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{'loss': 1.3708, 'learning_rate': 0.00039862661656346816, 'epoch': 0.07}

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{'loss': 1.2435, 'learning_rate': 0.00039860458022236, 'epoch': 0.07}

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{'loss': 1.2099, 'learning_rate': 0.0003985823691145548, 'epoch': 0.07}

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{'loss': 1.3541, 'learning_rate': 0.0003985599832595977, 'epoch': 0.07}

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{'loss': 1.3682, 'learning_rate': 0.00039853742267718776, 'epoch': 0.07}

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{'loss': 1.3608, 'learning_rate': 0.00039851468738717765, 'epoch': 0.07}

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{'loss': 1.4069, 'learning_rate': 0.00039849177740957373, 'epoch': 0.07}

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{'loss': 1.7075, 'learning_rate': 0.00039846869276453624, 'epoch': 0.07}

  7%|▋         | 232/3449 [10:53<2:30:51,  2.81s/it]
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{'loss': 1.257, 'learning_rate': 0.000398445433472379, 'epoch': 0.07}

  7%|▋         | 233/3449 [10:56<2:33:16,  2.86s/it]
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{'loss': 1.3831, 'learning_rate': 0.0003984219995535697, 'epoch': 0.07}

  7%|▋         | 234/3449 [10:58<2:24:55,  2.70s/it]
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{'loss': 1.3522, 'learning_rate': 0.00039839839102872936, 'epoch': 0.07}

  7%|▋         | 235/3449 [11:02<2:35:55,  2.91s/it]
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{'loss': 1.4216, 'learning_rate': 0.00039837460791863297, 'epoch': 0.07}

  7%|▋         | 236/3449 [11:04<2:28:36,  2.78s/it]
  7%|▋         | 237/3449 [11:07<2:31:59,  2.84s/it]
                                                    
{'loss': 1.3535, 'learning_rate': 0.000398350650244209, 'epoch': 0.07}

  7%|▋         | 237/3449 [11:07<2:31:59,  2.84s/it]
  7%|▋         | 238/3449 [11:09<2:24:22,  2.70s/it]
                                                    
{'loss': 1.3365, 'learning_rate': 0.0003983265180265396, 'epoch': 0.07}

  7%|▋         | 238/3449 [11:09<2:24:22,  2.70s/it]
  7%|▋         | 239/3449 [11:12<2:15:21,  2.53s/it]
                                                    
{'loss': 1.4763, 'learning_rate': 0.0003983022112868604, 'epoch': 0.07}

  7%|▋         | 239/3449 [11:12<2:15:21,  2.53s/it]
  7%|▋         | 240/3449 [11:15<2:22:03,  2.66s/it]
                                                    
{'loss': 1.3085, 'learning_rate': 0.0003982777300465608, 'epoch': 0.07}

  7%|▋         | 240/3449 [11:15<2:22:03,  2.66s/it]
  7%|▋         | 241/3449 [11:17<2:20:56,  2.64s/it]
                                                    
{'loss': 1.3435, 'learning_rate': 0.0003982530743271834, 'epoch': 0.07}

  7%|▋         | 241/3449 [11:17<2:20:56,  2.64s/it]
  7%|▋         | 242/3449 [11:20<2:17:32,  2.57s/it]
                                                    
{'loss': 1.1607, 'learning_rate': 0.0003982282441504248, 'epoch': 0.07}

  7%|▋         | 242/3449 [11:20<2:17:32,  2.57s/it]
  7%|▋         | 243/3449 [11:23<2:29:28,  2.80s/it]
                                                    
{'loss': 1.3848, 'learning_rate': 0.0003982032395381348, 'epoch': 0.07}

  7%|▋         | 243/3449 [11:23<2:29:28,  2.80s/it]
  7%|▋         | 244/3449 [11:25<2:24:36,  2.71s/it]
                                                    
{'loss': 1.5452, 'learning_rate': 0.00039817806051231685, 'epoch': 0.07}

  7%|▋         | 244/3449 [11:25<2:24:36,  2.71s/it]
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{'loss': 1.4223, 'learning_rate': 0.0003981527070951277, 'epoch': 0.07}

  7%|▋         | 245/3449 [11:28<2:22:34,  2.67s/it]
  7%|▋         | 246/3449 [11:31<2:23:58,  2.70s/it]
                                                    
{'loss': 1.5239, 'learning_rate': 0.00039812717930887777, 'epoch': 0.07}

  7%|▋         | 246/3449 [11:31<2:23:58,  2.70s/it]
  7%|▋         | 247/3449 [11:34<2:25:41,  2.73s/it]
                                                    
{'loss': 1.4098, 'learning_rate': 0.0003981014771760307, 'epoch': 0.07}

  7%|▋         | 247/3449 [11:34<2:25:41,  2.73s/it]
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{'loss': 1.2477, 'learning_rate': 0.0003980756007192039, 'epoch': 0.07}

  7%|▋         | 248/3449 [11:37<2:31:04,  2.83s/it]
  7%|▋         | 249/3449 [11:39<2:31:40,  2.84s/it]
                                                    
{'loss': 1.2293, 'learning_rate': 0.00039804954996116774, 'epoch': 0.07}

  7%|▋         | 249/3449 [11:39<2:31:40,  2.84s/it]
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{'loss': 1.2934, 'learning_rate': 0.0003980233249248463, 'epoch': 0.07}

  7%|▋         | 250/3449 [11:42<2:25:35,  2.73s/it]
  7%|▋         | 251/3449 [11:45<2:28:48,  2.79s/it]
                                                    
{'loss': 1.2993, 'learning_rate': 0.00039799692563331686, 'epoch': 0.07}

  7%|▋         | 251/3449 [11:45<2:28:48,  2.79s/it]
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{'loss': 1.4085, 'learning_rate': 0.0003979703521098102, 'epoch': 0.07}

  7%|▋         | 252/3449 [11:47<2:22:08,  2.67s/it]
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{'loss': 1.2628, 'learning_rate': 0.00039794360437771015, 'epoch': 0.07}

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{'loss': 1.4072, 'learning_rate': 0.00039791668246055406, 'epoch': 0.07}

  7%|▋         | 254/3449 [11:52<2:17:45,  2.59s/it]
  7%|▋         | 255/3449 [11:55<2:14:35,  2.53s/it]
                                                    
{'loss': 1.3316, 'learning_rate': 0.0003978895863820325, 'epoch': 0.07}

  7%|▋         | 255/3449 [11:55<2:14:35,  2.53s/it]
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{'loss': 1.3214, 'learning_rate': 0.00039786231616598935, 'epoch': 0.07}

  7%|▋         | 256/3449 [11:58<2:20:37,  2.64s/it]
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{'loss': 1.3406, 'learning_rate': 0.00039783487183642154, 'epoch': 0.07}

  7%|▋         | 257/3449 [12:00<2:17:08,  2.58s/it]
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{'loss': 1.5058, 'learning_rate': 0.00039780725341747946, 'epoch': 0.07}

  7%|▋         | 258/3449 [12:02<2:14:18,  2.53s/it]
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{'loss': 1.2867, 'learning_rate': 0.0003977794609334665, 'epoch': 0.08}

  8%|▊         | 259/3449 [12:06<2:24:07,  2.71s/it]
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{'loss': 1.3296, 'learning_rate': 0.00039775149440883934, 'epoch': 0.08}

  8%|▊         | 260/3449 [12:09<2:28:50,  2.80s/it]
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{'loss': 1.3374, 'learning_rate': 0.0003977233538682077, 'epoch': 0.08}

  8%|▊         | 261/3449 [12:11<2:22:35,  2.68s/it]
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{'loss': 1.3311, 'learning_rate': 0.0003976950393363346, 'epoch': 0.08}

  8%|▊         | 262/3449 [12:15<2:38:27,  2.98s/it]
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{'loss': 1.3599, 'learning_rate': 0.00039766655083813603, 'epoch': 0.08}

  8%|▊         | 263/3449 [12:17<2:32:17,  2.87s/it]
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{'loss': 1.2804, 'learning_rate': 0.0003976378883986811, 'epoch': 0.08}

  8%|▊         | 264/3449 [12:20<2:28:07,  2.79s/it]
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{'loss': 1.2712, 'learning_rate': 0.000397609052043192, 'epoch': 0.08}

  8%|▊         | 265/3449 [12:23<2:25:42,  2.75s/it]
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{'loss': 1.3557, 'learning_rate': 0.00039758004179704393, 'epoch': 0.08}

  8%|▊         | 266/3449 [12:25<2:23:39,  2.71s/it]
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{'loss': 1.2742, 'learning_rate': 0.0003975508576857651, 'epoch': 0.08}

  8%|▊         | 267/3449 [12:29<2:36:00,  2.94s/it]
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{'loss': 1.5171, 'learning_rate': 0.0003975214997350368, 'epoch': 0.08}

  8%|▊         | 268/3449 [12:31<2:29:02,  2.81s/it]
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{'loss': 1.4556, 'learning_rate': 0.00039749196797069316, 'epoch': 0.08}

  8%|▊         | 269/3449 [12:34<2:23:55,  2.72s/it]
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{'loss': 1.2967, 'learning_rate': 0.0003974622624187215, 'epoch': 0.08}

  8%|▊         | 270/3449 [12:37<2:38:25,  2.99s/it]
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{'loss': 1.3242, 'learning_rate': 0.00039743238310526173, 'epoch': 0.08}

  8%|▊         | 271/3449 [12:41<2:42:36,  3.07s/it]
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{'loss': 1.2761, 'learning_rate': 0.0003974023300566069, 'epoch': 0.08}

  8%|▊         | 272/3449 [12:43<2:36:10,  2.95s/it]
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{'loss': 1.3672, 'learning_rate': 0.0003973721032992029, 'epoch': 0.08}

  8%|▊         | 273/3449 [12:46<2:29:43,  2.83s/it]
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{'loss': 1.3849, 'learning_rate': 0.0003973417028596485, 'epoch': 0.08}

  8%|▊         | 274/3449 [12:49<2:32:10,  2.88s/it]
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{'loss': 1.3892, 'learning_rate': 0.00039731112876469527, 'epoch': 0.08}

  8%|▊         | 275/3449 [12:52<2:30:14,  2.84s/it]
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{'loss': 1.3909, 'learning_rate': 0.0003972803810412475, 'epoch': 0.08}

  8%|▊         | 276/3449 [12:54<2:30:03,  2.84s/it]
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{'loss': 1.407, 'learning_rate': 0.0003972494597163625, 'epoch': 0.08}

  8%|▊         | 277/3449 [12:57<2:31:03,  2.86s/it]
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{'loss': 1.3331, 'learning_rate': 0.00039721836481725, 'epoch': 0.08}

  8%|▊         | 278/3449 [13:00<2:35:45,  2.95s/it]
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{'loss': 1.4107, 'learning_rate': 0.00039718709637127285, 'epoch': 0.08}

  8%|▊         | 279/3449 [13:03<2:28:40,  2.81s/it]
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{'loss': 1.3444, 'learning_rate': 0.00039715565440594637, 'epoch': 0.08}

  8%|▊         | 280/3449 [13:06<2:29:27,  2.83s/it]
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{'loss': 1.3164, 'learning_rate': 0.00039712403894893875, 'epoch': 0.08}

  8%|▊         | 281/3449 [13:10<2:45:01,  3.13s/it]
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{'loss': 1.4395, 'learning_rate': 0.0003970922500280706, 'epoch': 0.08}

  8%|▊         | 282/3449 [13:13<2:47:33,  3.17s/it]
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{'loss': 1.4244, 'learning_rate': 0.00039706028767131545, 'epoch': 0.08}

  8%|▊         | 283/3449 [13:16<2:50:09,  3.22s/it]
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{'loss': 1.2813, 'learning_rate': 0.00039702815190679916, 'epoch': 0.08}

  8%|▊         | 284/3449 [13:20<3:03:20,  3.48s/it]
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{'loss': 1.427, 'learning_rate': 0.00039699584276280044, 'epoch': 0.08}

  8%|▊         | 285/3449 [13:23<2:52:03,  3.26s/it]
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{'loss': 1.1327, 'learning_rate': 0.00039696336026775043, 'epoch': 0.08}

  8%|▊         | 286/3449 [13:26<2:44:43,  3.12s/it]
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{'loss': 1.3982, 'learning_rate': 0.000396930704450233, 'epoch': 0.08}

  8%|▊         | 287/3449 [13:29<2:45:33,  3.14s/it]
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{'loss': 1.3648, 'learning_rate': 0.00039689787533898414, 'epoch': 0.08}

  8%|▊         | 288/3449 [13:32<2:49:03,  3.21s/it]
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{'loss': 1.3662, 'learning_rate': 0.0003968648729628927, 'epoch': 0.08}

  8%|▊         | 289/3449 [13:35<2:43:32,  3.11s/it]
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{'loss': 1.3564, 'learning_rate': 0.00039683169735099997, 'epoch': 0.08}

  8%|▊         | 290/3449 [13:38<2:33:51,  2.92s/it]
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{'loss': 1.3171, 'learning_rate': 0.00039679834853249954, 'epoch': 0.08}

  8%|▊         | 291/3449 [13:40<2:26:39,  2.79s/it]
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{'loss': 1.4295, 'learning_rate': 0.0003967648265367374, 'epoch': 0.08}

  8%|▊         | 292/3449 [13:43<2:21:21,  2.69s/it]
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{'loss': 1.2965, 'learning_rate': 0.00039673113139321217, 'epoch': 0.08}

  8%|▊         | 293/3449 [13:45<2:22:43,  2.71s/it]
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{'loss': 1.6415, 'learning_rate': 0.00039669726313157447, 'epoch': 0.09}

  9%|▊         | 294/3449 [13:48<2:14:35,  2.56s/it]
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{'loss': 1.2551, 'learning_rate': 0.00039666322178162763, 'epoch': 0.09}

  9%|▊         | 295/3449 [13:51<2:30:59,  2.87s/it]
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{'loss': 1.3234, 'learning_rate': 0.00039662900737332695, 'epoch': 0.09}

  9%|▊         | 296/3449 [13:55<2:47:55,  3.20s/it]
  9%|▊         | 297/3449 [13:58<2:42:30,  3.09s/it]
                                                    
{'loss': 1.3994, 'learning_rate': 0.0003965946199367804, 'epoch': 0.09}

  9%|▊         | 297/3449 [13:58<2:42:30,  3.09s/it]
  9%|▊         | 298/3449 [14:01<2:40:47,  3.06s/it]
                                                    
{'loss': 1.206, 'learning_rate': 0.0003965600595022478, 'epoch': 0.09}

  9%|▊         | 298/3449 [14:01<2:40:47,  3.06s/it]
  9%|▊         | 299/3449 [14:04<2:38:11,  3.01s/it]
                                                    
{'loss': 1.2827, 'learning_rate': 0.0003965253261001416, 'epoch': 0.09}

  9%|▊         | 299/3449 [14:04<2:38:11,  3.01s/it]
  9%|▊         | 300/3449 [14:07<2:33:46,  2.93s/it]
                                                    
{'loss': 1.3162, 'learning_rate': 0.0003964904197610261, 'epoch': 0.09}

  9%|▊         | 300/3449 [14:07<2:33:46,  2.93s/it]
  9%|▊         | 301/3449 [14:09<2:20:30,  2.68s/it]
                                                    
{'loss': 1.5978, 'learning_rate': 0.000396455340515618, 'epoch': 0.09}

  9%|▊         | 301/3449 [14:09<2:20:30,  2.68s/it]
  9%|▉         | 302/3449 [14:12<2:29:55,  2.86s/it]
                                                    
{'loss': 1.3232, 'learning_rate': 0.00039642008839478615, 'epoch': 0.09}

  9%|▉         | 302/3449 [14:12<2:29:55,  2.86s/it]
  9%|▉         | 303/3449 [14:15<2:27:49,  2.82s/it]
                                                    
{'loss': 1.2778, 'learning_rate': 0.0003963846634295513, 'epoch': 0.09}

  9%|▉         | 303/3449 [14:15<2:27:49,  2.82s/it]
  9%|▉         | 304/3449 [14:17<2:21:33,  2.70s/it]
                                                    
{'loss': 1.3913, 'learning_rate': 0.00039634906565108667, 'epoch': 0.09}

  9%|▉         | 304/3449 [14:17<2:21:33,  2.70s/it]
  9%|▉         | 305/3449 [14:21<2:36:22,  2.98s/it]
                                                    
{'loss': 1.2894, 'learning_rate': 0.00039631329509071724, 'epoch': 0.09}

  9%|▉         | 305/3449 [14:21<2:36:22,  2.98s/it]
  9%|▉         | 306/3449 [14:24<2:36:28,  2.99s/it]
                                                    
{'loss': 1.3261, 'learning_rate': 0.00039627735177992024, 'epoch': 0.09}

  9%|▉         | 306/3449 [14:24<2:36:28,  2.99s/it]
  9%|▉         | 307/3449 [14:27<2:33:47,  2.94s/it]
                                                    
{'loss': 1.3329, 'learning_rate': 0.0003962412357503246, 'epoch': 0.09}

  9%|▉         | 307/3449 [14:27<2:33:47,  2.94s/it]
  9%|▉         | 308/3449 [14:29<2:27:04,  2.81s/it]
                                                    
{'loss': 1.3168, 'learning_rate': 0.00039620494703371175, 'epoch': 0.09}

  9%|▉         | 308/3449 [14:29<2:27:04,  2.81s/it]
  9%|▉         | 309/3449 [14:33<2:36:00,  2.98s/it]
                                                    
{'loss': 1.3801, 'learning_rate': 0.00039616848566201453, 'epoch': 0.09}

  9%|▉         | 309/3449 [14:33<2:36:00,  2.98s/it]
  9%|▉         | 310/3449 [14:36<2:39:39,  3.05s/it]
                                                    
{'loss': 1.3349, 'learning_rate': 0.00039613185166731814, 'epoch': 0.09}

  9%|▉         | 310/3449 [14:36<2:39:39,  3.05s/it]
  9%|▉         | 311/3449 [14:39<2:39:53,  3.06s/it]
                                                    
{'loss': 1.2949, 'learning_rate': 0.00039609504508185937, 'epoch': 0.09}

  9%|▉         | 311/3449 [14:39<2:39:53,  3.06s/it]
  9%|▉         | 312/3449 [14:42<2:33:31,  2.94s/it]
                                                    
{'loss': 1.1931, 'learning_rate': 0.00039605806593802714, 'epoch': 0.09}

  9%|▉         | 312/3449 [14:42<2:33:31,  2.94s/it]
  9%|▉         | 313/3449 [14:44<2:27:45,  2.83s/it]
                                                    
{'loss': 1.5426, 'learning_rate': 0.00039602091426836205, 'epoch': 0.09}

  9%|▉         | 313/3449 [14:44<2:27:45,  2.83s/it]
  9%|▉         | 314/3449 [14:47<2:31:07,  2.89s/it]
                                                    
{'loss': 1.4269, 'learning_rate': 0.0003959835901055566, 'epoch': 0.09}

  9%|▉         | 314/3449 [14:47<2:31:07,  2.89s/it]
  9%|▉         | 315/3449 [14:50<2:31:09,  2.89s/it]
                                                    
{'loss': 1.3779, 'learning_rate': 0.00039594609348245506, 'epoch': 0.09}

  9%|▉         | 315/3449 [14:50<2:31:09,  2.89s/it]
  9%|▉         | 316/3449 [14:53<2:26:19,  2.80s/it]
                                                    
{'loss': 1.3227, 'learning_rate': 0.00039590842443205335, 'epoch': 0.09}

  9%|▉         | 316/3449 [14:53<2:26:19,  2.80s/it]
  9%|▉         | 317/3449 [14:56<2:34:46,  2.96s/it]
                                                    
{'loss': 1.331, 'learning_rate': 0.0003958705829874994, 'epoch': 0.09}

  9%|▉         | 317/3449 [14:56<2:34:46,  2.96s/it]
  9%|▉         | 318/3449 [14:59<2:35:01,  2.97s/it]
                                                    
{'loss': 1.2632, 'learning_rate': 0.0003958325691820925, 'epoch': 0.09}

  9%|▉         | 318/3449 [14:59<2:35:01,  2.97s/it]
  9%|▉         | 319/3449 [15:02<2:29:31,  2.87s/it]
                                                    
{'loss': 1.3223, 'learning_rate': 0.00039579438304928385, 'epoch': 0.09}

  9%|▉         | 319/3449 [15:02<2:29:31,  2.87s/it]
  9%|▉         | 320/3449 [15:04<2:22:31,  2.73s/it]
                                                    
{'loss': 1.396, 'learning_rate': 0.0003957560246226763, 'epoch': 0.09}

  9%|▉         | 320/3449 [15:04<2:22:31,  2.73s/it]
  9%|▉         | 321/3449 [15:08<2:41:15,  3.09s/it]
                                                    
{'loss': 1.3239, 'learning_rate': 0.00039571749393602405, 'epoch': 0.09}

  9%|▉         | 321/3449 [15:08<2:41:15,  3.09s/it]
  9%|▉         | 322/3449 [15:11<2:36:56,  3.01s/it]
                                                    
{'loss': 1.4516, 'learning_rate': 0.0003956787910232332, 'epoch': 0.09}

  9%|▉         | 322/3449 [15:11<2:36:56,  3.01s/it]
  9%|▉         | 323/3449 [15:15<2:57:40,  3.41s/it]
                                                    
{'loss': 1.3951, 'learning_rate': 0.00039563991591836127, 'epoch': 0.09}

  9%|▉         | 323/3449 [15:15<2:57:40,  3.41s/it]
  9%|▉         | 324/3449 [15:18<2:47:28,  3.22s/it]
                                                    
{'loss': 1.3145, 'learning_rate': 0.0003956008686556172, 'epoch': 0.09}

  9%|▉         | 324/3449 [15:18<2:47:28,  3.22s/it]
  9%|▉         | 325/3449 [15:21<2:48:56,  3.24s/it]
                                                    
{'loss': 1.298, 'learning_rate': 0.0003955616492693617, 'epoch': 0.09}

  9%|▉         | 325/3449 [15:21<2:48:56,  3.24s/it]
  9%|▉         | 326/3449 [15:23<2:34:39,  2.97s/it]
                                                    
{'loss': 1.3131, 'learning_rate': 0.0003955222577941067, 'epoch': 0.09}

  9%|▉         | 326/3449 [15:23<2:34:39,  2.97s/it]
  9%|▉         | 327/3449 [15:26<2:28:24,  2.85s/it]
                                                    
{'loss': 1.2039, 'learning_rate': 0.00039548269426451557, 'epoch': 0.09}

  9%|▉         | 327/3449 [15:26<2:28:24,  2.85s/it]
 10%|▉         | 328/3449 [15:29<2:33:56,  2.96s/it]
                                                    
{'loss': 1.3435, 'learning_rate': 0.0003954429587154032, 'epoch': 0.1}

 10%|▉         | 328/3449 [15:29<2:33:56,  2.96s/it]
 10%|▉         | 329/3449 [15:32<2:27:10,  2.83s/it]
                                                    
{'loss': 1.4773, 'learning_rate': 0.0003954030511817359, 'epoch': 0.1}

 10%|▉         | 329/3449 [15:32<2:27:10,  2.83s/it]
 10%|▉         | 330/3449 [15:35<2:28:12,  2.85s/it]
                                                    
{'loss': 1.4621, 'learning_rate': 0.0003953629716986311, 'epoch': 0.1}

 10%|▉         | 330/3449 [15:35<2:28:12,  2.85s/it]
 10%|▉         | 331/3449 [15:38<2:32:46,  2.94s/it]
                                                    
{'loss': 1.4583, 'learning_rate': 0.0003953227203013577, 'epoch': 0.1}

 10%|▉         | 331/3449 [15:38<2:32:46,  2.94s/it]
 10%|▉         | 332/3449 [15:40<2:26:52,  2.83s/it]
                                                    
{'loss': 1.4588, 'learning_rate': 0.0003952822970253359, 'epoch': 0.1}

 10%|▉         | 332/3449 [15:40<2:26:52,  2.83s/it]
 10%|▉         | 333/3449 [15:43<2:19:12,  2.68s/it]
                                                    
{'loss': 1.3788, 'learning_rate': 0.0003952417019061371, 'epoch': 0.1}

 10%|▉         | 333/3449 [15:43<2:19:12,  2.68s/it]
 10%|▉         | 334/3449 [15:45<2:18:03,  2.66s/it]
                                                    
{'loss': 1.3653, 'learning_rate': 0.0003952009349794838, 'epoch': 0.1}

 10%|▉         | 334/3449 [15:45<2:18:03,  2.66s/it]
 10%|▉         | 335/3449 [15:48<2:18:23,  2.67s/it]
                                                    
{'loss': 1.2425, 'learning_rate': 0.0003951599962812499, 'epoch': 0.1}

 10%|▉         | 335/3449 [15:48<2:18:23,  2.67s/it]
 10%|▉         | 336/3449 [15:51<2:19:15,  2.68s/it]
                                                    
{'loss': 1.2731, 'learning_rate': 0.00039511888584746035, 'epoch': 0.1}

 10%|▉         | 336/3449 [15:51<2:19:15,  2.68s/it]
 10%|▉         | 337/3449 [15:53<2:13:13,  2.57s/it]
                                                    
{'loss': 1.3504, 'learning_rate': 0.00039507760371429126, 'epoch': 0.1}

 10%|▉         | 337/3449 [15:53<2:13:13,  2.57s/it]
 10%|▉         | 338/3449 [15:56<2:19:24,  2.69s/it]
                                                    
{'loss': 1.3654, 'learning_rate': 0.0003950361499180697, 'epoch': 0.1}

 10%|▉         | 338/3449 [15:56<2:19:24,  2.69s/it]
 10%|▉         | 339/3449 [16:00<2:39:12,  3.07s/it]
                                                    
{'loss': 1.3129, 'learning_rate': 0.00039499452449527395, 'epoch': 0.1}

 10%|▉         | 339/3449 [16:00<2:39:12,  3.07s/it]
 10%|▉         | 340/3449 [16:02<2:27:20,  2.84s/it]
                                                    
{'loss': 1.4244, 'learning_rate': 0.00039495272748253326, 'epoch': 0.1}

 10%|▉         | 340/3449 [16:02<2:27:20,  2.84s/it]
 10%|▉         | 341/3449 [16:05<2:24:22,  2.79s/it]
                                                    
{'loss': 1.41, 'learning_rate': 0.00039491075891662794, 'epoch': 0.1}

 10%|▉         | 341/3449 [16:05<2:24:22,  2.79s/it]
 10%|▉         | 342/3449 [16:08<2:23:07,  2.76s/it]
                                                    
{'loss': 1.2094, 'learning_rate': 0.00039486861883448907, 'epoch': 0.1}

 10%|▉         | 342/3449 [16:08<2:23:07,  2.76s/it]
 10%|▉         | 343/3449 [16:10<2:16:04,  2.63s/it]
                                                    
{'loss': 1.5471, 'learning_rate': 0.00039482630727319883, 'epoch': 0.1}

 10%|▉         | 343/3449 [16:10<2:16:04,  2.63s/it]
 10%|▉         | 344/3449 [16:13<2:17:00,  2.65s/it]
                                                    
{'loss': 1.2915, 'learning_rate': 0.0003947838242699904, 'epoch': 0.1}

 10%|▉         | 344/3449 [16:13<2:17:00,  2.65s/it]
 10%|█         | 345/3449 [16:16<2:20:09,  2.71s/it]
                                                    
{'loss': 1.3057, 'learning_rate': 0.0003947411698622475, 'epoch': 0.1}

 10%|█         | 345/3449 [16:16<2:20:09,  2.71s/it]
 10%|█         | 346/3449 [16:18<2:17:19,  2.66s/it]
                                                    
{'loss': 1.374, 'learning_rate': 0.000394698344087505, 'epoch': 0.1}

 10%|█         | 346/3449 [16:18<2:17:19,  2.66s/it]
 10%|█         | 347/3449 [16:21<2:23:59,  2.79s/it]
                                                    
{'loss': 1.3786, 'learning_rate': 0.00039465534698344826, 'epoch': 0.1}

 10%|█         | 347/3449 [16:21<2:23:59,  2.79s/it]
 10%|█         | 348/3449 [16:24<2:28:11,  2.87s/it]
                                                    
{'loss': 1.4415, 'learning_rate': 0.0003946121785879138, 'epoch': 0.1}

 10%|█         | 348/3449 [16:24<2:28:11,  2.87s/it]
 10%|█         | 349/3449 [16:28<2:36:43,  3.03s/it]
                                                    
{'loss': 1.2374, 'learning_rate': 0.00039456883893888845, 'epoch': 0.1}

 10%|█         | 349/3449 [16:28<2:36:43,  3.03s/it]
 10%|█         | 350/3449 [16:30<2:27:45,  2.86s/it]
                                                    
{'loss': 1.3662, 'learning_rate': 0.00039452532807451006, 'epoch': 0.1}

 10%|█         | 350/3449 [16:30<2:27:45,  2.86s/it]
 10%|█         | 351/3449 [16:33<2:26:05,  2.83s/it]
                                                    
{'loss': 1.2629, 'learning_rate': 0.0003944816460330669, 'epoch': 0.1}

 10%|█         | 351/3449 [16:33<2:26:05,  2.83s/it]
 10%|█         | 352/3449 [16:35<2:22:40,  2.76s/it]
                                                    
{'loss': 1.2885, 'learning_rate': 0.00039443779285299824, 'epoch': 0.1}

 10%|█         | 352/3449 [16:35<2:22:40,  2.76s/it]
 10%|█         | 353/3449 [16:39<2:30:16,  2.91s/it]
                                                    
{'loss': 1.3265, 'learning_rate': 0.0003943937685728934, 'epoch': 0.1}

 10%|█         | 353/3449 [16:39<2:30:16,  2.91s/it]
 10%|█         | 354/3449 [16:42<2:40:18,  3.11s/it]
                                                    
{'loss': 1.2861, 'learning_rate': 0.00039434957323149277, 'epoch': 0.1}

 10%|█         | 354/3449 [16:42<2:40:18,  3.11s/it]
 10%|█         | 355/3449 [16:45<2:30:21,  2.92s/it]
                                                    
{'loss': 1.27, 'learning_rate': 0.00039430520686768695, 'epoch': 0.1}

 10%|█         | 355/3449 [16:45<2:30:21,  2.92s/it]
 10%|█         | 356/3449 [16:48<2:32:10,  2.95s/it]
                                                    
{'loss': 1.1879, 'learning_rate': 0.0003942606695205172, 'epoch': 0.1}

 10%|█         | 356/3449 [16:48<2:32:10,  2.95s/it]
 10%|█         | 357/3449 [16:50<2:26:03,  2.83s/it]
                                                    
{'loss': 1.4018, 'learning_rate': 0.0003942159612291752, 'epoch': 0.1}

 10%|█         | 357/3449 [16:50<2:26:03,  2.83s/it]
 10%|█         | 358/3449 [16:54<2:33:42,  2.98s/it]
                                                    
{'loss': 1.3663, 'learning_rate': 0.000394171082033003, 'epoch': 0.1}

 10%|█         | 358/3449 [16:54<2:33:42,  2.98s/it]
 10%|█         | 359/3449 [16:56<2:29:14,  2.90s/it]
                                                    
{'loss': 1.2719, 'learning_rate': 0.0003941260319714932, 'epoch': 0.1}

 10%|█         | 359/3449 [16:56<2:29:14,  2.90s/it]
 10%|█         | 360/3449 [16:59<2:26:09,  2.84s/it]
                                                    
{'loss': 1.3557, 'learning_rate': 0.00039408081108428843, 'epoch': 0.1}

 10%|█         | 360/3449 [16:59<2:26:09,  2.84s/it]
 10%|█         | 361/3449 [17:02<2:25:03,  2.82s/it]
                                                    
{'loss': 1.251, 'learning_rate': 0.0003940354194111821, 'epoch': 0.1}

 10%|█         | 361/3449 [17:02<2:25:03,  2.82s/it]
 10%|█         | 362/3449 [17:04<2:22:06,  2.76s/it]
                                                    
{'loss': 1.4242, 'learning_rate': 0.0003939898569921175, 'epoch': 0.1}

 10%|█         | 362/3449 [17:04<2:22:06,  2.76s/it]
 11%|█         | 363/3449 [17:07<2:16:48,  2.66s/it]
                                                    
{'loss': 1.464, 'learning_rate': 0.0003939441238671884, 'epoch': 0.11}

 11%|█         | 363/3449 [17:07<2:16:48,  2.66s/it]
 11%|█         | 364/3449 [17:09<2:13:09,  2.59s/it]
                                                    
{'loss': 1.279, 'learning_rate': 0.00039389822007663866, 'epoch': 0.11}

 11%|█         | 364/3449 [17:09<2:13:09,  2.59s/it]
 11%|█         | 365/3449 [17:12<2:13:04,  2.59s/it]
                                                    
{'loss': 1.4705, 'learning_rate': 0.0003938521456608625, 'epoch': 0.11}

 11%|█         | 365/3449 [17:12<2:13:04,  2.59s/it]
 11%|█         | 366/3449 [17:14<2:11:59,  2.57s/it]
                                                    
{'loss': 1.2939, 'learning_rate': 0.000393805900660404, 'epoch': 0.11}

 11%|█         | 366/3449 [17:14<2:11:59,  2.57s/it]
 11%|█         | 367/3449 [17:17<2:13:04,  2.59s/it]
                                                    
{'loss': 1.3762, 'learning_rate': 0.0003937594851159577, 'epoch': 0.11}

 11%|█         | 367/3449 [17:17<2:13:04,  2.59s/it]
 11%|█         | 368/3449 [17:20<2:22:30,  2.78s/it]
                                                    
{'loss': 1.504, 'learning_rate': 0.00039371289906836793, 'epoch': 0.11}

 11%|█         | 368/3449 [17:20<2:22:30,  2.78s/it]
 11%|█         | 369/3449 [17:23<2:27:26,  2.87s/it]
                                                    
{'loss': 1.1273, 'learning_rate': 0.00039366614255862916, 'epoch': 0.11}

 11%|█         | 369/3449 [17:23<2:27:26,  2.87s/it]
 11%|█         | 370/3449 [17:26<2:24:24,  2.81s/it]
                                                    
{'loss': 1.2929, 'learning_rate': 0.00039361921562788594, 'epoch': 0.11}

 11%|█         | 370/3449 [17:26<2:24:24,  2.81s/it]
 11%|█         | 371/3449 [17:29<2:25:02,  2.83s/it]
                                                    
{'loss': 1.461, 'learning_rate': 0.0003935721183174326, 'epoch': 0.11}

 11%|█         | 371/3449 [17:29<2:25:02,  2.83s/it]
 11%|█         | 372/3449 [17:32<2:23:15,  2.79s/it]
                                                    
{'loss': 1.2933, 'learning_rate': 0.00039352485066871355, 'epoch': 0.11}

 11%|█         | 372/3449 [17:32<2:23:15,  2.79s/it]
 11%|█         | 373/3449 [17:35<2:35:07,  3.03s/it]
                                                    
{'loss': 1.2856, 'learning_rate': 0.0003934774127233231, 'epoch': 0.11}

 11%|█         | 373/3449 [17:35<2:35:07,  3.03s/it]
 11%|█         | 374/3449 [17:38<2:32:10,  2.97s/it]
                                                    
{'loss': 1.3504, 'learning_rate': 0.0003934298045230053, 'epoch': 0.11}

 11%|█         | 374/3449 [17:38<2:32:10,  2.97s/it]
 11%|█         | 375/3449 [17:40<2:24:17,  2.82s/it]
                                                    
{'loss': 1.3782, 'learning_rate': 0.0003933820261096541, 'epoch': 0.11}

 11%|█         | 375/3449 [17:40<2:24:17,  2.82s/it]
 11%|█         | 376/3449 [17:43<2:23:32,  2.80s/it]
                                                    
{'loss': 1.2738, 'learning_rate': 0.00039333407752531333, 'epoch': 0.11}

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{'loss': 1.4028, 'learning_rate': 0.00039328595881217625, 'epoch': 0.11}

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{'loss': 1.3697, 'learning_rate': 0.0003932376700125862, 'epoch': 0.11}

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{'loss': 1.471, 'learning_rate': 0.000393189211169036, 'epoch': 0.11}

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{'loss': 1.4331, 'learning_rate': 0.0003931405823241681, 'epoch': 0.11}

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{'loss': 1.3678, 'learning_rate': 0.00039309178352077455, 'epoch': 0.11}

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{'loss': 1.2892, 'learning_rate': 0.0003930428148017971, 'epoch': 0.11}

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{'loss': 1.381, 'learning_rate': 0.00039299367621032673, 'epoch': 0.11}

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{'loss': 1.255, 'learning_rate': 0.0003929443677896042, 'epoch': 0.11}

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{'loss': 1.5373, 'learning_rate': 0.00039289488958301963, 'epoch': 0.11}

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{'loss': 1.4048, 'learning_rate': 0.0003928452416341124, 'epoch': 0.11}

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{'loss': 1.3485, 'learning_rate': 0.0003927954239865715, 'epoch': 0.11}

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{'loss': 1.3841, 'learning_rate': 0.00039274543668423495, 'epoch': 0.11}

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{'loss': 1.2156, 'learning_rate': 0.00039269527977109044, 'epoch': 0.11}

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{'loss': 1.4647, 'learning_rate': 0.0003926449532912746, 'epoch': 0.11}

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{'loss': 1.3239, 'learning_rate': 0.00039259445728907327, 'epoch': 0.11}

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{'loss': 1.2882, 'learning_rate': 0.0003925437918089218, 'epoch': 0.11}

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{'loss': 1.3821, 'learning_rate': 0.00039249295689540426, 'epoch': 0.11}

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{'loss': 1.1908, 'learning_rate': 0.00039244195259325416, 'epoch': 0.11}

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{'loss': 1.1618, 'learning_rate': 0.00039239077894735383, 'epoch': 0.11}

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{'loss': 1.3317, 'learning_rate': 0.0003923394360027347, 'epoch': 0.11}

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{'loss': 1.5053, 'learning_rate': 0.0003922879238045773, 'epoch': 0.12}

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{'loss': 1.3213, 'learning_rate': 0.00039223624239821073, 'epoch': 0.12}

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{'loss': 1.1913, 'learning_rate': 0.0003921843918291135, 'epoch': 0.12}

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{'loss': 1.3521, 'learning_rate': 0.0003921323721429126, 'epoch': 0.12}

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{'loss': 1.4003, 'learning_rate': 0.00039208018338538386, 'epoch': 0.12}

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{'loss': 1.2853, 'learning_rate': 0.0003920278256024522, 'epoch': 0.12}

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{'loss': 1.6179, 'learning_rate': 0.00039197529884019096, 'epoch': 0.12}

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{'loss': 1.3391, 'learning_rate': 0.00039192260314482223, 'epoch': 0.12}

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{'loss': 1.3379, 'learning_rate': 0.00039186973856271683, 'epoch': 0.12}

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{'loss': 1.2994, 'learning_rate': 0.0003918167051403943, 'epoch': 0.12}

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{'loss': 1.3591, 'learning_rate': 0.00039176350292452244, 'epoch': 0.12}

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{'loss': 1.259, 'learning_rate': 0.00039171013196191793, 'epoch': 0.12}

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{'loss': 1.402, 'learning_rate': 0.00039165659229954566, 'epoch': 0.12}

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{'loss': 1.2868, 'learning_rate': 0.00039160288398451906, 'epoch': 0.12}

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{'loss': 1.4592, 'learning_rate': 0.0003915490070641002, 'epoch': 0.12}

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{'loss': 1.3848, 'learning_rate': 0.00039149496158569924, 'epoch': 0.12}

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{'loss': 1.292, 'learning_rate': 0.0003914407475968746, 'epoch': 0.12}

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{'loss': 1.2964, 'learning_rate': 0.0003913863651453333, 'epoch': 0.12}

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{'loss': 1.2426, 'learning_rate': 0.00039133181427893044, 'epoch': 0.12}

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{'loss': 1.3032, 'learning_rate': 0.0003912770950456693, 'epoch': 0.12}

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{'loss': 1.427, 'learning_rate': 0.00039122220749370125, 'epoch': 0.12}

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{'loss': 1.1978, 'learning_rate': 0.00039116715167132593, 'epoch': 0.12}

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{'loss': 1.3663, 'learning_rate': 0.00039111192762699093, 'epoch': 0.12}

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{'loss': 1.2532, 'learning_rate': 0.00039105653540929197, 'epoch': 0.12}

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{'loss': 1.2392, 'learning_rate': 0.00039100097506697276, 'epoch': 0.12}

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{'loss': 1.2665, 'learning_rate': 0.00039094524664892483, 'epoch': 0.12}

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{'loss': 1.2964, 'learning_rate': 0.00039088935020418776, 'epoch': 0.12}

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{'loss': 1.3515, 'learning_rate': 0.0003908332857819488, 'epoch': 0.12}

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{'loss': 1.4667, 'learning_rate': 0.0003907770534315433, 'epoch': 0.12}

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{'loss': 1.2508, 'learning_rate': 0.00039072065320245415, 'epoch': 0.12}

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{'loss': 1.1843, 'learning_rate': 0.000390664085144312, 'epoch': 0.12}

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{'loss': 1.2708, 'learning_rate': 0.0003906073493068952, 'epoch': 0.12}

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{'loss': 1.2819, 'learning_rate': 0.0003905504457401299, 'epoch': 0.12}

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{'loss': 1.3026, 'learning_rate': 0.00039049337449408955, 'epoch': 0.12}

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{'loss': 1.3789, 'learning_rate': 0.0003904361356189954, 'epoch': 0.12}

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{'loss': 1.324, 'learning_rate': 0.00039037872916521614, 'epoch': 0.13}

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{'loss': 1.4777, 'learning_rate': 0.0003903211551832678, 'epoch': 0.13}

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{'loss': 1.3832, 'learning_rate': 0.0003902634137238141, 'epoch': 0.13}

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{'loss': 1.2534, 'learning_rate': 0.00039020550483766583, 'epoch': 0.13}

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{'loss': 1.3532, 'learning_rate': 0.0003901474285757813, 'epoch': 0.13}

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{'loss': 1.1942, 'learning_rate': 0.0003900891849892661, 'epoch': 0.13}

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{'loss': 1.3259, 'learning_rate': 0.000390030774129373, 'epoch': 0.13}

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{'loss': 1.3383, 'learning_rate': 0.00038997219604750195, 'epoch': 0.13}

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{'loss': 1.3872, 'learning_rate': 0.00038991345079520014, 'epoch': 0.13}

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{'loss': 1.2964, 'learning_rate': 0.00038985453842416183, 'epoch': 0.13}

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{'loss': 1.4885, 'learning_rate': 0.0003897954589862282, 'epoch': 0.13}

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{'loss': 1.1836, 'learning_rate': 0.00038973621253338776, 'epoch': 0.13}

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{'loss': 1.3709, 'learning_rate': 0.0003896767991177757, 'epoch': 0.13}

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{'loss': 1.3361, 'learning_rate': 0.0003896172187916741, 'epoch': 0.13}

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{'loss': 1.4199, 'learning_rate': 0.0003895574716075123, 'epoch': 0.13}

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{'loss': 1.3185, 'learning_rate': 0.00038949755761786604, 'epoch': 0.13}

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{'loss': 1.4701, 'learning_rate': 0.0003894374768754581, 'epoch': 0.13}

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{'loss': 1.2512, 'learning_rate': 0.0003893772294331578, 'epoch': 0.13}

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{'loss': 1.4217, 'learning_rate': 0.00038931681534398147, 'epoch': 0.13}

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{'loss': 1.393, 'learning_rate': 0.00038925623466109176, 'epoch': 0.13}

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{'loss': 1.4419, 'learning_rate': 0.00038919548743779803, 'epoch': 0.13}

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{'loss': 1.2372, 'learning_rate': 0.00038913457372755626, 'epoch': 0.13}

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{'loss': 1.4241, 'learning_rate': 0.0003890734935839688, 'epoch': 0.13}

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{'loss': 1.3903, 'learning_rate': 0.0003890122470607847, 'epoch': 0.13}

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{'loss': 1.1638, 'learning_rate': 0.00038895083421189904, 'epoch': 0.13}

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{'loss': 1.3148, 'learning_rate': 0.00038888925509135365, 'epoch': 0.13}

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{'loss': 1.3197, 'learning_rate': 0.00038882750975333645, 'epoch': 0.13}

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{'loss': 1.3027, 'learning_rate': 0.00038876559825218164, 'epoch': 0.13}

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{'loss': 1.2378, 'learning_rate': 0.0003887035206423697, 'epoch': 0.13}

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{'loss': 1.2874, 'learning_rate': 0.0003886412769785273, 'epoch': 0.13}

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{'loss': 1.3247, 'learning_rate': 0.0003885788673154272, 'epoch': 0.13}

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{'loss': 1.4948, 'learning_rate': 0.0003885162917079881, 'epoch': 0.13}

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{'loss': 1.3641, 'learning_rate': 0.00038845355021127495, 'epoch': 0.13}

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{'loss': 1.2692, 'learning_rate': 0.0003883906428804986, 'epoch': 0.13}

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{'loss': 1.2695, 'learning_rate': 0.00038832756977101574, 'epoch': 0.14}

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{'loss': 1.3523, 'learning_rate': 0.00038826433093832913, 'epoch': 0.14}

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{'loss': 1.4101, 'learning_rate': 0.0003882009264380871, 'epoch': 0.14}

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{'loss': 1.1302, 'learning_rate': 0.0003881373563260841, 'epoch': 0.14}

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{'loss': 1.4, 'learning_rate': 0.0003880736206582599, 'epoch': 0.14}

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{'loss': 1.2677, 'learning_rate': 0.0003880097194907003, 'epoch': 0.14}

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{'loss': 1.2799, 'learning_rate': 0.00038794565287963653, 'epoch': 0.14}

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{'loss': 1.4191, 'learning_rate': 0.00038788142088144566, 'epoch': 0.14}

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{'loss': 1.1316, 'learning_rate': 0.00038781702355264995, 'epoch': 0.14}

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{'loss': 1.3546, 'learning_rate': 0.00038775246094991734, 'epoch': 0.14}

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{'loss': 1.2596, 'learning_rate': 0.0003876877331300613, 'epoch': 0.14}

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{'loss': 1.5291, 'learning_rate': 0.0003876228401500404, 'epoch': 0.14}

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{'loss': 1.4081, 'learning_rate': 0.0003875577820669589, 'epoch': 0.14}

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{'loss': 1.2045, 'learning_rate': 0.0003874925589380661, 'epoch': 0.14}

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{'loss': 1.3115, 'learning_rate': 0.0003874271708207565, 'epoch': 0.14}

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{'loss': 1.3006, 'learning_rate': 0.00038736161777257004, 'epoch': 0.14}

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{'loss': 1.2511, 'learning_rate': 0.00038729589985119156, 'epoch': 0.14}

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{'loss': 1.3153, 'learning_rate': 0.0003872300171144511, 'epoch': 0.14}

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{'loss': 1.5334, 'learning_rate': 0.00038716396962032364, 'epoch': 0.14}

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{'loss': 1.3983, 'learning_rate': 0.00038709775742692927, 'epoch': 0.14}

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{'loss': 1.2143, 'learning_rate': 0.0003870313805925329, 'epoch': 0.14}

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{'loss': 1.3641, 'learning_rate': 0.0003869648391755444, 'epoch': 0.14}

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{'loss': 1.4607, 'learning_rate': 0.00038689813323451836, 'epoch': 0.14}

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{'loss': 1.2097, 'learning_rate': 0.0003868312628281543, 'epoch': 0.14}

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{'loss': 1.2142, 'learning_rate': 0.0003867642280152963, 'epoch': 0.14}

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{'loss': 1.1171, 'learning_rate': 0.0003866970288549333, 'epoch': 0.14}

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{'loss': 1.3582, 'learning_rate': 0.0003866296654061986, 'epoch': 0.14}

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{'loss': 1.2705, 'learning_rate': 0.00038656213772837045, 'epoch': 0.14}

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{'loss': 1.0947, 'learning_rate': 0.00038649444588087115, 'epoch': 0.14}

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{'loss': 1.3349, 'learning_rate': 0.00038642658992326794, 'epoch': 0.14}

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{'loss': 1.3444, 'learning_rate': 0.00038635856991527204, 'epoch': 0.14}

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{'loss': 1.2091, 'learning_rate': 0.0003862903859167393, 'epoch': 0.14}

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{'loss': 1.3876, 'learning_rate': 0.00038622203798766984, 'epoch': 0.14}

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{'loss': 1.3659, 'learning_rate': 0.000386153526188208, 'epoch': 0.14}

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{'loss': 1.3617, 'learning_rate': 0.00038608485057864227, 'epoch': 0.14}

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{'loss': 1.3491, 'learning_rate': 0.0003860160112194054, 'epoch': 0.15}

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{'loss': 1.2504, 'learning_rate': 0.00038594700817107415, 'epoch': 0.15}

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{'loss': 1.297, 'learning_rate': 0.0003858778414943694, 'epoch': 0.15}

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{'loss': 1.4889, 'learning_rate': 0.00038580851125015583, 'epoch': 0.15}

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{'loss': 1.3215, 'learning_rate': 0.0003857390174994424, 'epoch': 0.15}

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{'loss': 1.336, 'learning_rate': 0.00038566936030338153, 'epoch': 0.15}

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{'loss': 1.4424, 'learning_rate': 0.00038559953972326985, 'epoch': 0.15}

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{'loss': 1.3839, 'learning_rate': 0.0003855295558205475, 'epoch': 0.15}

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{'loss': 1.4157, 'learning_rate': 0.00038545940865679845, 'epoch': 0.15}

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{'loss': 1.3802, 'learning_rate': 0.00038538909829375034, 'epoch': 0.15}

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{'loss': 1.4247, 'learning_rate': 0.0003853186247932744, 'epoch': 0.15}

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{'loss': 1.2501, 'learning_rate': 0.0003852479882173854, 'epoch': 0.15}

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{'loss': 1.3293, 'learning_rate': 0.00038517718862824166, 'epoch': 0.15}

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{'loss': 1.3841, 'learning_rate': 0.00038510622608814486, 'epoch': 0.15}

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{'loss': 1.3453, 'learning_rate': 0.00038503510065954026, 'epoch': 0.15}

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{'loss': 1.2539, 'learning_rate': 0.00038496381240501614, 'epoch': 0.15}

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{'loss': 1.2811, 'learning_rate': 0.0003848923613873044, 'epoch': 0.15}

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{'loss': 1.3435, 'learning_rate': 0.00038482074766927997, 'epoch': 0.15}

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{'loss': 1.2876, 'learning_rate': 0.0003847489713139609, 'epoch': 0.15}

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{'loss': 1.185, 'learning_rate': 0.00038467703238450864, 'epoch': 0.15}

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{'loss': 1.196, 'learning_rate': 0.00038460493094422734, 'epoch': 0.15}

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{'loss': 1.3964, 'learning_rate': 0.0003845326670565645, 'epoch': 0.15}

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{'loss': 1.4147, 'learning_rate': 0.0003844602407851103, 'epoch': 0.15}

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{'loss': 1.352, 'learning_rate': 0.0003843876521935979, 'epoch': 0.15}

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{'loss': 1.2607, 'learning_rate': 0.00038431490134590337, 'epoch': 0.15}

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{'loss': 1.2796, 'learning_rate': 0.0003842419883060454, 'epoch': 0.15}

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{'loss': 1.3396, 'learning_rate': 0.0003841689131381856, 'epoch': 0.15}

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{'loss': 1.4369, 'learning_rate': 0.0003840956759066282, 'epoch': 0.15}

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{'loss': 1.5503, 'learning_rate': 0.0003840222766758198, 'epoch': 0.15}

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{'loss': 1.3106, 'learning_rate': 0.00038394871551035003, 'epoch': 0.15}

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{'loss': 1.3839, 'learning_rate': 0.0003838749924749505, 'epoch': 0.15}

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{'loss': 1.3257, 'learning_rate': 0.00038380110763449563, 'epoch': 0.15}

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{'loss': 1.4503, 'learning_rate': 0.00038372706105400207, 'epoch': 0.15}

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{'loss': 1.2723, 'learning_rate': 0.00038365285279862876, 'epoch': 0.15}

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{'loss': 1.4161, 'learning_rate': 0.000383578482933677, 'epoch': 0.16}

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{'loss': 1.1735, 'learning_rate': 0.0003835039515245904, 'epoch': 0.16}

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{'loss': 1.2848, 'learning_rate': 0.0003834292586369545, 'epoch': 0.16}

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{'loss': 1.3721, 'learning_rate': 0.00038335440433649693, 'epoch': 0.16}

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{'loss': 1.3287, 'learning_rate': 0.00038327938868908763, 'epoch': 0.16}

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{'loss': 1.5261, 'learning_rate': 0.00038320421176073823, 'epoch': 0.16}

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{'loss': 1.3888, 'learning_rate': 0.0003831288736176025, 'epoch': 0.16}

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{'loss': 1.3134, 'learning_rate': 0.000383053374325976, 'epoch': 0.16}

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{'loss': 1.3813, 'learning_rate': 0.00038297771395229594, 'epoch': 0.16}

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{'loss': 1.2592, 'learning_rate': 0.00038290189256314156, 'epoch': 0.16}

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{'loss': 1.2625, 'learning_rate': 0.00038282591022523356, 'epoch': 0.16}

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{'loss': 1.2192, 'learning_rate': 0.0003827497670054344, 'epoch': 0.16}

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{'loss': 1.2154, 'learning_rate': 0.0003826734629707481, 'epoch': 0.16}

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{'loss': 1.3196, 'learning_rate': 0.0003825969981883201, 'epoch': 0.16}

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{'loss': 1.3649, 'learning_rate': 0.00038252037272543734, 'epoch': 0.16}

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{'loss': 1.2522, 'learning_rate': 0.0003824435866495282, 'epoch': 0.16}

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{'loss': 1.2861, 'learning_rate': 0.00038236664002816244, 'epoch': 0.16}

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{'loss': 1.3513, 'learning_rate': 0.00038228953292905094, 'epoch': 0.16}

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{'loss': 1.2638, 'learning_rate': 0.0003822122654200458, 'epoch': 0.16}

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{'loss': 1.2824, 'learning_rate': 0.0003821348375691405, 'epoch': 0.16}

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{'loss': 1.4368, 'learning_rate': 0.0003820572494444694, 'epoch': 0.16}

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{'loss': 1.3823, 'learning_rate': 0.00038197950111430794, 'epoch': 0.16}

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{'loss': 1.4946, 'learning_rate': 0.00038190159264707267, 'epoch': 0.16}

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{'loss': 1.3771, 'learning_rate': 0.00038182352411132085, 'epoch': 0.16}

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{'loss': 1.367, 'learning_rate': 0.0003817452955757507, 'epoch': 0.16}

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{'loss': 1.2109, 'learning_rate': 0.00038166690710920124, 'epoch': 0.16}

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{'loss': 1.1682, 'learning_rate': 0.00038158835878065225, 'epoch': 0.16}

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{'loss': 1.2641, 'learning_rate': 0.0003815096506592241, 'epoch': 0.16}

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{'loss': 1.4155, 'learning_rate': 0.0003814307828141779, 'epoch': 0.16}

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{'loss': 1.4218, 'learning_rate': 0.00038135175531491515, 'epoch': 0.16}

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{'loss': 1.198, 'learning_rate': 0.00038127256823097794, 'epoch': 0.16}

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{'loss': 1.3554, 'learning_rate': 0.00038119322163204886, 'epoch': 0.16}

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{'loss': 1.1691, 'learning_rate': 0.00038111371558795064, 'epoch': 0.16}

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{'loss': 1.326, 'learning_rate': 0.0003810340501686466, 'epoch': 0.16}

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{'loss': 1.4071, 'learning_rate': 0.0003809542254442401, 'epoch': 0.16}

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{'loss': 1.3133, 'learning_rate': 0.0003808742414849748, 'epoch': 0.17}

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{'loss': 1.3361, 'learning_rate': 0.0003807940983612344, 'epoch': 0.17}

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{'loss': 1.2362, 'learning_rate': 0.0003807137961435427, 'epoch': 0.17}

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{'loss': 1.431, 'learning_rate': 0.00038063333490256354, 'epoch': 0.17}

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{'loss': 1.2436, 'learning_rate': 0.00038055271470910053, 'epoch': 0.17}

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{'loss': 1.2789, 'learning_rate': 0.00038047193563409744, 'epoch': 0.17}

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{'loss': 1.2921, 'learning_rate': 0.00038039099774863754, 'epoch': 0.17}

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{'loss': 1.2558, 'learning_rate': 0.00038030990112394413, 'epoch': 0.17}

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{'loss': 1.3656, 'learning_rate': 0.0003802286458313799, 'epoch': 0.17}

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{'loss': 1.2975, 'learning_rate': 0.00038014723194244746, 'epoch': 0.17}

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{'loss': 1.3769, 'learning_rate': 0.0003800656595287888, 'epoch': 0.17}

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{'loss': 1.2094, 'learning_rate': 0.0003799020394145584, 'epoch': 0.17}

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{'loss': 1.3608, 'learning_rate': 0.0003798199918579679, 'epoch': 0.17}

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{'loss': 1.2369, 'learning_rate': 0.0003797377860646138, 'epoch': 0.17}

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{'loss': 1.3911, 'learning_rate': 0.00037965542210683474, 'epoch': 0.17}

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{'loss': 1.292, 'learning_rate': 0.000379572900057109, 'epoch': 0.17}

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{'loss': 1.3406, 'learning_rate': 0.0003794902199880536, 'epoch': 0.17}

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{'loss': 1.2936, 'learning_rate': 0.0003794073819724249, 'epoch': 0.17}

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{'loss': 1.529, 'learning_rate': 0.0003793243860831181, 'epoch': 0.17}

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{'loss': 1.2682, 'learning_rate': 0.00037915792097574557, 'epoch': 0.17}

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{'loss': 1.4804, 'learning_rate': 0.0003790744519041647, 'epoch': 0.17}

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{'loss': 1.2158, 'learning_rate': 0.00037899082525187525, 'epoch': 0.17}

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{'loss': 1.3411, 'learning_rate': 0.0003789070410924664, 'epoch': 0.17}

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{'loss': 1.2307, 'learning_rate': 0.00037882309949966597, 'epoch': 0.17}

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{'loss': 1.2769, 'learning_rate': 0.00037873900054734034, 'epoch': 0.17}

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{'loss': 1.4223, 'learning_rate': 0.00037865474430949427, 'epoch': 0.17}

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{'loss': 1.2942, 'learning_rate': 0.00037857033086027104, 'epoch': 0.17}

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{'loss': 1.2689, 'learning_rate': 0.0003784857602739522, 'epoch': 0.17}

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{'loss': 1.3241, 'learning_rate': 0.0003784010326249576, 'epoch': 0.17}

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{'loss': 1.222, 'learning_rate': 0.00037831614798784525, 'epoch': 0.17}

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{'loss': 1.3674, 'learning_rate': 0.0003782311064373114, 'epoch': 0.17}

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{'loss': 1.4221, 'learning_rate': 0.0003781459080481903, 'epoch': 0.17}

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{'loss': 1.4172, 'learning_rate': 0.0003780605528954543, 'epoch': 0.18}

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{'loss': 1.3146, 'learning_rate': 0.0003779750410542136, 'epoch': 0.18}

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{'loss': 1.2114, 'learning_rate': 0.0003778893725997163, 'epoch': 0.18}

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{'loss': 1.2844, 'learning_rate': 0.00037780354760734837, 'epoch': 0.18}

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{'loss': 1.3779, 'learning_rate': 0.0003777175661526336, 'epoch': 0.18}

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{'loss': 1.0988, 'learning_rate': 0.0003776314283112331, 'epoch': 0.18}

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{'loss': 1.3803, 'learning_rate': 0.0003775451341589461, 'epoch': 0.18}

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{'loss': 1.1517, 'learning_rate': 0.00037745868377170907, 'epoch': 0.18}

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{'loss': 1.2965, 'learning_rate': 0.000377372077225596, 'epoch': 0.18}

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{'loss': 1.4926, 'learning_rate': 0.00037728531459681826, 'epoch': 0.18}

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{'loss': 1.4066, 'learning_rate': 0.00037719839596172476, 'epoch': 0.18}

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{'loss': 1.3498, 'learning_rate': 0.00037711132139680155, 'epoch': 0.18}

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{'loss': 1.4738, 'learning_rate': 0.00037702409097867186, 'epoch': 0.18}

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{'loss': 1.3854, 'learning_rate': 0.00037693670478409607, 'epoch': 0.18}

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{'loss': 1.2015, 'learning_rate': 0.00037684916288997176, 'epoch': 0.18}

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{'loss': 1.3336, 'learning_rate': 0.00037676146537333344, 'epoch': 0.18}

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{'loss': 1.2285, 'learning_rate': 0.00037667361231135256, 'epoch': 0.18}

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{'loss': 1.3738, 'learning_rate': 0.00037658560378133745, 'epoch': 0.18}

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{'loss': 1.2951, 'learning_rate': 0.0003764974398607333, 'epoch': 0.18}

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{'loss': 1.3998, 'learning_rate': 0.00037640912062712186, 'epoch': 0.18}

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{'loss': 1.3421, 'learning_rate': 0.00037632064615822185, 'epoch': 0.18}

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{'loss': 1.2505, 'learning_rate': 0.0003762320165318883, 'epoch': 0.18}

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{'loss': 1.3863, 'learning_rate': 0.000376143231826113, 'epoch': 0.18}

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{'loss': 1.2849, 'learning_rate': 0.00037605429211902397, 'epoch': 0.18}

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{'loss': 1.221, 'learning_rate': 0.00037596519748888594, 'epoch': 0.18}

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{'loss': 1.195, 'learning_rate': 0.0003758759480140997, 'epoch': 0.18}

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{'loss': 1.4152, 'learning_rate': 0.0003757865437732023, 'epoch': 0.18}

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{'loss': 1.3788, 'learning_rate': 0.00037569698484486724, 'epoch': 0.18}

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{'loss': 1.2949, 'learning_rate': 0.00037560727130790385, 'epoch': 0.18}

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{'loss': 1.3709, 'learning_rate': 0.00037551740324125773, 'epoch': 0.18}

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{'loss': 1.2895, 'learning_rate': 0.00037542738072401027, 'epoch': 0.18}

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{'loss': 1.3311, 'learning_rate': 0.0003753372038353789, 'epoch': 0.18}

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{'loss': 1.2309, 'learning_rate': 0.00037524687265471697, 'epoch': 0.18}

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{'loss': 1.3925, 'learning_rate': 0.0003751563872615133, 'epoch': 0.18}

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{'loss': 1.3566, 'learning_rate': 0.00037506574773539276, 'epoch': 0.18}

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{'loss': 1.3243, 'learning_rate': 0.0003749749541561156, 'epoch': 0.19}

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{'loss': 1.3834, 'learning_rate': 0.00037488400660357774, 'epoch': 0.19}

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{'loss': 1.2708, 'learning_rate': 0.00037479290515781067, 'epoch': 0.19}

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{'loss': 1.3351, 'learning_rate': 0.00037470164989898116, 'epoch': 0.19}

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{'loss': 1.3267, 'learning_rate': 0.00037461024090739136, 'epoch': 0.19}

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{'loss': 1.3807, 'learning_rate': 0.00037451867826347876, 'epoch': 0.19}

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{'loss': 1.1451, 'learning_rate': 0.00037442696204781605, 'epoch': 0.19}

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{'loss': 1.2059, 'learning_rate': 0.000374335092341111, 'epoch': 0.19}

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{'loss': 1.1875, 'learning_rate': 0.0003742430692242065, 'epoch': 0.19}

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{'loss': 1.4249, 'learning_rate': 0.0003741508927780804, 'epoch': 0.19}

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{'loss': 1.4409, 'learning_rate': 0.0003740585630838455, 'epoch': 0.19}

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{'loss': 1.4722, 'learning_rate': 0.0003739660802227495, 'epoch': 0.19}

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{'loss': 1.2156, 'learning_rate': 0.00037387344427617476, 'epoch': 0.19}

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{'loss': 1.3374, 'learning_rate': 0.00037378065532563847, 'epoch': 0.19}

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{'loss': 1.24, 'learning_rate': 0.00037368771345279244, 'epoch': 0.19}

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{'loss': 1.3434, 'learning_rate': 0.00037359461873942297, 'epoch': 0.19}

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{'loss': 1.3179, 'learning_rate': 0.0003735013712674509, 'epoch': 0.19}

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{'loss': 1.3183, 'learning_rate': 0.0003734079711189316, 'epoch': 0.19}

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{'loss': 1.2632, 'learning_rate': 0.0003733144183760546, 'epoch': 0.19}

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{'loss': 1.4223, 'learning_rate': 0.0003732207131211438, 'epoch': 0.19}

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{'loss': 1.3397, 'learning_rate': 0.0003731268554366573, 'epoch': 0.19}

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{'loss': 1.2703, 'learning_rate': 0.00037303284540518745, 'epoch': 0.19}

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{'loss': 1.5002, 'learning_rate': 0.00037293868310946045, 'epoch': 0.19}

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{'loss': 1.3052, 'learning_rate': 0.00037284436863233657, 'epoch': 0.19}

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{'loss': 1.3705, 'learning_rate': 0.0003727499020568101, 'epoch': 0.19}

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{'loss': 1.4041, 'learning_rate': 0.00037265528346600913, 'epoch': 0.19}

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{'loss': 1.1651, 'learning_rate': 0.0003725605129431953, 'epoch': 0.19}

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{'loss': 1.3479, 'learning_rate': 0.0003724655905717643, 'epoch': 0.19}

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{'loss': 1.2762, 'learning_rate': 0.0003723705164352451, 'epoch': 0.19}

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{'loss': 1.2119, 'learning_rate': 0.00037227529061730055, 'epoch': 0.19}

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{'loss': 1.3735, 'learning_rate': 0.00037217991320172674, 'epoch': 0.19}

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{'loss': 1.288, 'learning_rate': 0.0003720843842724532, 'epoch': 0.19}

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{'loss': 1.3138, 'learning_rate': 0.0003719887039135429, 'epoch': 0.19}

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{'loss': 1.3225, 'learning_rate': 0.000371892872209192, 'epoch': 0.19}

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{'loss': 1.2151, 'learning_rate': 0.0003717968892437297, 'epoch': 0.2}

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{'loss': 1.3943, 'learning_rate': 0.00037170075510161853, 'epoch': 0.2}

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{'loss': 1.3298, 'learning_rate': 0.0003716044698674539, 'epoch': 0.2}

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{'loss': 1.2433, 'learning_rate': 0.0003715080336259643, 'epoch': 0.2}

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{'loss': 1.2967, 'learning_rate': 0.000371411446462011, 'epoch': 0.2}

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{'loss': 1.3173, 'learning_rate': 0.0003713147084605881, 'epoch': 0.2}

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{'loss': 1.3028, 'learning_rate': 0.0003712178197068224, 'epoch': 0.2}

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{'loss': 1.2044, 'learning_rate': 0.00037112078028597343, 'epoch': 0.2}

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{'loss': 1.1363, 'learning_rate': 0.00037102359028343335, 'epoch': 0.2}

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{'loss': 1.4618, 'learning_rate': 0.0003709262497847267, 'epoch': 0.2}

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{'loss': 1.3237, 'learning_rate': 0.00037082875887551047, 'epoch': 0.2}

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{'loss': 1.2146, 'learning_rate': 0.0003707311176415741, 'epoch': 0.2}

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{'loss': 1.2813, 'learning_rate': 0.0003706333261688392, 'epoch': 0.2}

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{'loss': 1.1922, 'learning_rate': 0.0003705353845433597, 'epoch': 0.2}

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  warnings.warn(

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{'loss': 1.2586, 'learning_rate': 0.00018079920598182794, 'epoch': 0.54}

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{'loss': 1.2424, 'learning_rate': 0.00018061246728003958, 'epoch': 0.54}

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{'loss': 1.2856, 'learning_rate': 0.00018042574563875935, 'epoch': 0.54}

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{'loss': 1.2349, 'learning_rate': 0.00018023904122229734, 'epoch': 0.55}

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{'loss': 1.2043, 'learning_rate': 0.00018005235419494832, 'epoch': 0.55}

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{'loss': 1.3362, 'learning_rate': 0.00017986568472099196, 'epoch': 0.55}

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{'loss': 1.2164, 'learning_rate': 0.00017967903296469234, 'epoch': 0.55}

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{'loss': 1.1486, 'learning_rate': 0.0001794923990902979, 'epoch': 0.55}

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{'loss': 1.3329, 'learning_rate': 0.00017930578326204156, 'epoch': 0.55}

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{'loss': 1.0274, 'learning_rate': 0.00017911918564414027, 'epoch': 0.55}

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{'loss': 1.3219, 'learning_rate': 0.00017893260640079473, 'epoch': 0.55}

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{'loss': 1.2519, 'learning_rate': 0.0001787460456961899, 'epoch': 0.55}

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{'loss': 1.2589, 'learning_rate': 0.00017855950369449408, 'epoch': 0.55}

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{'loss': 1.3642, 'learning_rate': 0.00017837298055985916, 'epoch': 0.55}

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{'loss': 0.9672, 'learning_rate': 0.00017818647645642061, 'epoch': 0.55}

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{'loss': 1.2383, 'learning_rate': 0.0001779999915482969, 'epoch': 0.55}

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{'loss': 1.3419, 'learning_rate': 0.00017781352599958983, 'epoch': 0.55}

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{'loss': 1.2397, 'learning_rate': 0.00017762707997438413, 'epoch': 0.55}

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{'loss': 1.221, 'learning_rate': 0.00017744065363674717, 'epoch': 0.55}

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{'loss': 1.3259, 'learning_rate': 0.0001772542471507291, 'epoch': 0.55}

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{'loss': 1.3263, 'learning_rate': 0.0001770678606803628, 'epoch': 0.55}

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{'loss': 1.2401, 'learning_rate': 0.0001768814943896632, 'epoch': 0.55}

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{'loss': 1.176, 'learning_rate': 0.0001766951484426277, 'epoch': 0.55}

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{'loss': 1.2862, 'learning_rate': 0.00017650882300323576, 'epoch': 0.55}

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{'loss': 1.2146, 'learning_rate': 0.00017632251823544866, 'epoch': 0.55}

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{'loss': 1.2925, 'learning_rate': 0.0001761362343032097, 'epoch': 0.55}

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{'loss': 1.281, 'learning_rate': 0.00017594997137044364, 'epoch': 0.55}

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{'loss': 1.0849, 'learning_rate': 0.00017576372960105687, 'epoch': 0.55}

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{'loss': 1.3125, 'learning_rate': 0.00017557750915893732, 'epoch': 0.55}

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{'loss': 1.1598, 'learning_rate': 0.00017539131020795367, 'epoch': 0.55}

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{'loss': 1.204, 'learning_rate': 0.00017520513291195626, 'epoch': 0.55}

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{'loss': 1.2307, 'learning_rate': 0.00017501897743477603, 'epoch': 0.55}

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{'loss': 1.2054, 'learning_rate': 0.0001748328439402247, 'epoch': 0.55}

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{'loss': 1.2374, 'learning_rate': 0.0001746467325920949, 'epoch': 0.55}

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{'loss': 1.3456, 'learning_rate': 0.00017446064355415957, 'epoch': 0.55}

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{'loss': 1.2549, 'learning_rate': 0.000174274576990172, 'epoch': 0.55}

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{'loss': 1.3875, 'learning_rate': 0.00017408853306386579, 'epoch': 0.55}

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{'loss': 1.413, 'learning_rate': 0.00017390251193895472, 'epoch': 0.55}

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{'loss': 1.2291, 'learning_rate': 0.00017371651377913225, 'epoch': 0.56}

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{'loss': 1.2189, 'learning_rate': 0.00017353053874807182, 'epoch': 0.56}

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{'loss': 1.1537, 'learning_rate': 0.00017334458700942644, 'epoch': 0.56}

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{'loss': 1.3019, 'learning_rate': 0.00017315865872682856, 'epoch': 0.56}

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{'loss': 1.2471, 'learning_rate': 0.00017297275406389032, 'epoch': 0.56}

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{'loss': 1.3551, 'learning_rate': 0.00017278687318420262, 'epoch': 0.56}

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{'loss': 1.2943, 'learning_rate': 0.00017260101625133563, 'epoch': 0.56}

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{'loss': 1.3282, 'learning_rate': 0.0001724151834288387, 'epoch': 0.56}

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{'loss': 1.5019, 'learning_rate': 0.0001722293748802394, 'epoch': 0.56}

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{'loss': 1.2648, 'learning_rate': 0.00017204359076904445, 'epoch': 0.56}

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{'loss': 1.1127, 'learning_rate': 0.00017185783125873893, 'epoch': 0.56}

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{'loss': 1.272, 'learning_rate': 0.00017167209651278604, 'epoch': 0.56}

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{'loss': 1.1037, 'learning_rate': 0.0001714863866946276, 'epoch': 0.56}

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{'loss': 1.2949, 'learning_rate': 0.00017130070196768297, 'epoch': 0.56}

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{'loss': 1.2811, 'learning_rate': 0.00017111504249534996, 'epoch': 0.56}

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{'loss': 1.1952, 'learning_rate': 0.00017092940844100387, 'epoch': 0.56}

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{'loss': 1.2638, 'learning_rate': 0.00017074379996799758, 'epoch': 0.56}

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{'loss': 1.1908, 'learning_rate': 0.0001705582172396617, 'epoch': 0.56}

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{'loss': 1.2415, 'learning_rate': 0.00017037266041930398, 'epoch': 0.56}

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{'loss': 1.3337, 'learning_rate': 0.00017018712967020941, 'epoch': 0.56}

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{'loss': 1.2085, 'learning_rate': 0.00017000162515564007, 'epoch': 0.56}

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{'loss': 1.2212, 'learning_rate': 0.00016981614703883506, 'epoch': 0.56}

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{'loss': 1.1379, 'learning_rate': 0.00016963069548301004, 'epoch': 0.56}

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{'loss': 1.2124, 'learning_rate': 0.00016944527065135742, 'epoch': 0.56}

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{'loss': 1.1204, 'learning_rate': 0.00016925987270704606, 'epoch': 0.56}

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{'loss': 1.2249, 'learning_rate': 0.00016907450181322115, 'epoch': 0.56}

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{'loss': 1.2513, 'learning_rate': 0.0001688891581330042, 'epoch': 0.56}

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{'loss': 1.3299, 'learning_rate': 0.00016870384182949256, 'epoch': 0.56}

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{'loss': 1.3036, 'learning_rate': 0.00016851855306575963, 'epoch': 0.56}

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{'loss': 1.2294, 'learning_rate': 0.00016833329200485465, 'epoch': 0.56}

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{'loss': 1.2135, 'learning_rate': 0.0001681480588098022, 'epoch': 0.56}

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{'loss': 1.1569, 'learning_rate': 0.00016796285364360263, 'epoch': 0.56}

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{'loss': 1.1965, 'learning_rate': 0.00016777767666923156, 'epoch': 0.56}

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{'loss': 1.1513, 'learning_rate': 0.00016759252804963954, 'epoch': 0.56}

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{'loss': 1.1926, 'learning_rate': 0.0001674074079477526, 'epoch': 0.57}

 57%|█████▋    | 1949/3449 [1:31:55<1:12:39,  2.91s/it]
 57%|█████▋    | 1950/3449 [1:31:58<1:11:47,  2.87s/it]
                                                       
{'loss': 1.189, 'learning_rate': 0.00016722231652647145, 'epoch': 0.57}

 57%|█████▋    | 1950/3449 [1:31:58<1:11:47,  2.87s/it]
 57%|█████▋    | 1951/3449 [1:32:01<1:14:30,  2.98s/it]
                                                       
{'loss': 1.114, 'learning_rate': 0.00016703725394867145, 'epoch': 0.57}

 57%|█████▋    | 1951/3449 [1:32:01<1:14:30,  2.98s/it]
 57%|█████▋    | 1952/3449 [1:32:04<1:14:46,  3.00s/it]
                                                       
{'loss': 1.3933, 'learning_rate': 0.00016685222037720278, 'epoch': 0.57}

 57%|█████▋    | 1952/3449 [1:32:04<1:14:46,  3.00s/it]
 57%|█████▋    | 1953/3449 [1:32:07<1:13:45,  2.96s/it]
                                                       
{'loss': 1.1315, 'learning_rate': 0.00016666721597488992, 'epoch': 0.57}

 57%|█████▋    | 1953/3449 [1:32:07<1:13:45,  2.96s/it]
 57%|█████▋    | 1954/3449 [1:32:11<1:20:56,  3.25s/it]
                                                       
{'loss': 1.2984, 'learning_rate': 0.00016648224090453186, 'epoch': 0.57}

 57%|█████▋    | 1954/3449 [1:32:11<1:20:56,  3.25s/it]
 57%|█████▋    | 1955/3449 [1:32:14<1:16:25,  3.07s/it]
                                                       
{'loss': 1.4407, 'learning_rate': 0.00016629729532890175, 'epoch': 0.57}

 57%|█████▋    | 1955/3449 [1:32:14<1:16:25,  3.07s/it]
 57%|█████▋    | 1956/3449 [1:32:17<1:13:52,  2.97s/it]
                                                       
{'loss': 1.1905, 'learning_rate': 0.0001661123794107466, 'epoch': 0.57}

 57%|█████▋    | 1956/3449 [1:32:17<1:13:52,  2.97s/it]
 57%|█████▋    | 1957/3449 [1:32:19<1:08:58,  2.77s/it]
                                                       
{'loss': 1.1534, 'learning_rate': 0.00016592749331278747, 'epoch': 0.57}

 57%|█████▋    | 1957/3449 [1:32:19<1:08:58,  2.77s/it]
 57%|█████▋    | 1958/3449 [1:32:21<1:06:02,  2.66s/it]
                                                       
{'loss': 1.2697, 'learning_rate': 0.00016574263719771928, 'epoch': 0.57}

 57%|█████▋    | 1958/3449 [1:32:21<1:06:02,  2.66s/it]
 57%|█████▋    | 1959/3449 [1:32:24<1:05:38,  2.64s/it]
                                                       
{'loss': 1.3054, 'learning_rate': 0.00016555781122821035, 'epoch': 0.57}

 57%|█████▋    | 1959/3449 [1:32:24<1:05:38,  2.64s/it]
 57%|█████▋    | 1960/3449 [1:32:26<1:05:02,  2.62s/it]
                                                       
{'loss': 1.2623, 'learning_rate': 0.00016537301556690252, 'epoch': 0.57}

 57%|█████▋    | 1960/3449 [1:32:26<1:05:02,  2.62s/it]
 57%|█████▋    | 1961/3449 [1:32:29<1:08:03,  2.74s/it]
                                                       
{'loss': 1.2823, 'learning_rate': 0.0001651882503764112, 'epoch': 0.57}

 57%|█████▋    | 1961/3449 [1:32:29<1:08:03,  2.74s/it]
 57%|█████▋    | 1962/3449 [1:32:32<1:05:09,  2.63s/it]
                                                       
{'loss': 1.2938, 'learning_rate': 0.00016500351581932456, 'epoch': 0.57}

 57%|█████▋    | 1962/3449 [1:32:32<1:05:09,  2.63s/it]
 57%|█████▋    | 1963/3449 [1:32:35<1:07:03,  2.71s/it]
                                                       
{'loss': 1.279, 'learning_rate': 0.00016481881205820424, 'epoch': 0.57}

 57%|█████▋    | 1963/3449 [1:32:35<1:07:03,  2.71s/it]
 57%|█████▋    | 1964/3449 [1:32:37<1:06:41,  2.69s/it]
                                                       
{'loss': 1.1894, 'learning_rate': 0.00016463413925558445, 'epoch': 0.57}

 57%|█████▋    | 1964/3449 [1:32:37<1:06:41,  2.69s/it]
 57%|█████▋    | 1965/3449 [1:32:40<1:04:13,  2.60s/it]
                                                       
{'loss': 1.1466, 'learning_rate': 0.00016444949757397234, 'epoch': 0.57}

 57%|█████▋    | 1965/3449 [1:32:40<1:04:13,  2.60s/it]
 57%|█████▋    | 1966/3449 [1:32:42<1:03:16,  2.56s/it]
                                                       
{'loss': 1.3923, 'learning_rate': 0.00016426488717584777, 'epoch': 0.57}

 57%|█████▋    | 1966/3449 [1:32:42<1:03:16,  2.56s/it]
 57%|█████▋    | 1967/3449 [1:32:45<1:04:35,  2.61s/it]
                                                       
{'loss': 1.2416, 'learning_rate': 0.0001640803082236627, 'epoch': 0.57}

 57%|█████▋    | 1967/3449 [1:32:45<1:04:35,  2.61s/it]
 57%|█████▋    | 1968/3449 [1:32:47<1:03:37,  2.58s/it]
                                                       
{'loss': 1.2472, 'learning_rate': 0.00016389576087984177, 'epoch': 0.57}

 57%|█████▋    | 1968/3449 [1:32:47<1:03:37,  2.58s/it]
 57%|█████▋    | 1969/3449 [1:32:51<1:10:41,  2.87s/it]
                                                       
{'loss': 1.0552, 'learning_rate': 0.00016371124530678176, 'epoch': 0.57}

 57%|█████▋    | 1969/3449 [1:32:51<1:10:41,  2.87s/it]
 57%|█████▋    | 1970/3449 [1:32:53<1:07:44,  2.75s/it]
                                                       
{'loss': 1.4276, 'learning_rate': 0.00016352676166685122, 'epoch': 0.57}

 57%|█████▋    | 1970/3449 [1:32:53<1:07:44,  2.75s/it]
 57%|█████▋    | 1971/3449 [1:32:56<1:07:19,  2.73s/it]
                                                       
{'loss': 1.3438, 'learning_rate': 0.00016334231012239098, 'epoch': 0.57}

 57%|█████▋    | 1971/3449 [1:32:56<1:07:19,  2.73s/it]
 57%|█████▋    | 1972/3449 [1:32:59<1:08:19,  2.78s/it]
                                                       
{'loss': 1.3187, 'learning_rate': 0.00016315789083571342, 'epoch': 0.57}

 57%|█████▋    | 1972/3449 [1:32:59<1:08:19,  2.78s/it]
 57%|█████▋    | 1973/3449 [1:33:02<1:12:02,  2.93s/it]
                                                       
{'loss': 1.1763, 'learning_rate': 0.00016297350396910247, 'epoch': 0.57}

 57%|█████▋    | 1973/3449 [1:33:02<1:12:02,  2.93s/it]
 57%|█████▋    | 1974/3449 [1:33:05<1:10:52,  2.88s/it]
                                                       
{'loss': 1.2755, 'learning_rate': 0.00016278914968481374, 'epoch': 0.57}

 57%|█████▋    | 1974/3449 [1:33:05<1:10:52,  2.88s/it]
 57%|█████▋    | 1975/3449 [1:33:08<1:09:28,  2.83s/it]
                                                       
{'loss': 1.247, 'learning_rate': 0.00016260482814507387, 'epoch': 0.57}

 57%|█████▋    | 1975/3449 [1:33:08<1:09:28,  2.83s/it]
 57%|█████▋    | 1976/3449 [1:33:10<1:06:41,  2.72s/it]
                                                       
{'loss': 1.2318, 'learning_rate': 0.00016242053951208104, 'epoch': 0.57}

 57%|█████▋    | 1976/3449 [1:33:10<1:06:41,  2.72s/it]
 57%|█████▋    | 1977/3449 [1:33:13<1:07:09,  2.74s/it]
                                                       
{'loss': 1.215, 'learning_rate': 0.00016223628394800425, 'epoch': 0.57}

 57%|█████▋    | 1977/3449 [1:33:13<1:07:09,  2.74s/it]
 57%|█████▋    | 1978/3449 [1:33:16<1:04:55,  2.65s/it]
                                                       
{'loss': 1.0413, 'learning_rate': 0.00016205206161498342, 'epoch': 0.57}

 57%|█████▋    | 1978/3449 [1:33:16<1:04:55,  2.65s/it]
 57%|█████▋    | 1979/3449 [1:33:18<1:03:44,  2.60s/it]
                                                       
{'loss': 1.4229, 'learning_rate': 0.00016186787267512918, 'epoch': 0.57}

 57%|█████▋    | 1979/3449 [1:33:18<1:03:44,  2.60s/it]
 57%|█████▋    | 1980/3449 [1:33:21<1:03:15,  2.58s/it]
                                                       
{'loss': 1.2017, 'learning_rate': 0.00016168371729052307, 'epoch': 0.57}

 57%|█████▋    | 1980/3449 [1:33:21<1:03:15,  2.58s/it]
 57%|█████▋    | 1981/3449 [1:33:23<1:05:51,  2.69s/it]
                                                       
{'loss': 1.2663, 'learning_rate': 0.00016149959562321672, 'epoch': 0.57}

 57%|█████▋    | 1981/3449 [1:33:23<1:05:51,  2.69s/it]
 57%|█████▋    | 1982/3449 [1:33:26<1:05:46,  2.69s/it]
                                                       
{'loss': 1.1215, 'learning_rate': 0.0001613155078352322, 'epoch': 0.57}

 57%|█████▋    | 1982/3449 [1:33:26<1:05:46,  2.69s/it]
 57%|█████▋    | 1983/3449 [1:33:29<1:09:06,  2.83s/it]
                                                       
{'loss': 1.1153, 'learning_rate': 0.00016113145408856207, 'epoch': 0.57}

 57%|█████▋    | 1983/3449 [1:33:29<1:09:06,  2.83s/it]
 58%|█████▊    | 1984/3449 [1:33:33<1:14:15,  3.04s/it]
                                                       
{'loss': 1.1303, 'learning_rate': 0.0001609474345451684, 'epoch': 0.58}

 58%|█████▊    | 1984/3449 [1:33:33<1:14:15,  3.04s/it]
 58%|█████▊    | 1985/3449 [1:33:36<1:17:39,  3.18s/it]
                                                       
{'loss': 1.1184, 'learning_rate': 0.00016076344936698356, 'epoch': 0.58}

 58%|█████▊    | 1985/3449 [1:33:36<1:17:39,  3.18s/it]
 58%|█████▊    | 1986/3449 [1:33:39<1:15:55,  3.11s/it]
                                                       
{'loss': 1.2001, 'learning_rate': 0.00016057949871590963, 'epoch': 0.58}

 58%|█████▊    | 1986/3449 [1:33:39<1:15:55,  3.11s/it]
 58%|█████▊    | 1987/3449 [1:33:43<1:19:43,  3.27s/it]
                                                       
{'loss': 1.2126, 'learning_rate': 0.00016039558275381813, 'epoch': 0.58}

 58%|█████▊    | 1987/3449 [1:33:43<1:19:43,  3.27s/it]
 58%|█████▊    | 1988/3449 [1:33:45<1:12:09,  2.96s/it]
                                                       
{'loss': 1.2566, 'learning_rate': 0.00016021170164255027, 'epoch': 0.58}

 58%|█████▊    | 1988/3449 [1:33:45<1:12:09,  2.96s/it]
 58%|█████▊    | 1989/3449 [1:33:48<1:09:10,  2.84s/it]
                                                       
{'loss': 1.2464, 'learning_rate': 0.00016002785554391642, 'epoch': 0.58}

 58%|█████▊    | 1989/3449 [1:33:48<1:09:10,  2.84s/it]
 58%|█████▊    | 1990/3449 [1:33:50<1:05:22,  2.69s/it]
                                                       
{'loss': 1.3024, 'learning_rate': 0.00015984404461969623, 'epoch': 0.58}

 58%|█████▊    | 1990/3449 [1:33:50<1:05:22,  2.69s/it]
 58%|█████▊    | 1991/3449 [1:33:53<1:03:47,  2.63s/it]
                                                       
{'loss': 1.2382, 'learning_rate': 0.0001596602690316384, 'epoch': 0.58}

 58%|█████▊    | 1991/3449 [1:33:53<1:03:47,  2.63s/it]
 58%|█████▊    | 1992/3449 [1:33:56<1:08:27,  2.82s/it]
                                                       
{'loss': 1.2314, 'learning_rate': 0.0001594765289414604, 'epoch': 0.58}

 58%|█████▊    | 1992/3449 [1:33:56<1:08:27,  2.82s/it]
 58%|█████▊    | 1993/3449 [1:33:59<1:08:38,  2.83s/it]
                                                       
{'loss': 1.2229, 'learning_rate': 0.00015929282451084876, 'epoch': 0.58}

 58%|█████▊    | 1993/3449 [1:33:59<1:08:38,  2.83s/it]
 58%|█████▊    | 1994/3449 [1:34:02<1:10:03,  2.89s/it]
                                                       
{'loss': 1.3042, 'learning_rate': 0.00015910915590145835, 'epoch': 0.58}

 58%|█████▊    | 1994/3449 [1:34:02<1:10:03,  2.89s/it]
 58%|█████▊    | 1995/3449 [1:34:04<1:08:08,  2.81s/it]
                                                       
{'loss': 1.3198, 'learning_rate': 0.0001589255232749126, 'epoch': 0.58}

 58%|█████▊    | 1995/3449 [1:34:04<1:08:08,  2.81s/it]
 58%|█████▊    | 1996/3449 [1:34:07<1:04:59,  2.68s/it]
                                                       
{'loss': 1.4086, 'learning_rate': 0.00015874192679280323, 'epoch': 0.58}

 58%|█████▊    | 1996/3449 [1:34:07<1:04:59,  2.68s/it]
 58%|█████▊    | 1997/3449 [1:34:10<1:08:54,  2.85s/it]
                                                       
{'loss': 1.1759, 'learning_rate': 0.0001585583666166904, 'epoch': 0.58}

 58%|█████▊    | 1997/3449 [1:34:10<1:08:54,  2.85s/it]
 58%|█████▊    | 1998/3449 [1:34:12<1:05:59,  2.73s/it]
                                                       
{'loss': 1.2343, 'learning_rate': 0.00015837484290810196, 'epoch': 0.58}

 58%|█████▊    | 1998/3449 [1:34:12<1:05:59,  2.73s/it]
 58%|█████▊    | 1999/3449 [1:34:15<1:06:34,  2.75s/it]
                                                       
{'loss': 1.2502, 'learning_rate': 0.00015819135582853395, 'epoch': 0.58}

 58%|█████▊    | 1999/3449 [1:34:15<1:06:34,  2.75s/it]
 58%|█████▊    | 2000/3449 [1:34:19<1:11:52,  2.98s/it]
                                                       
{'loss': 1.2231, 'learning_rate': 0.00015800790553945003, 'epoch': 0.58}

 58%|█████▊    | 2000/3449 [1:34:19<1:11:52,  2.98s/it]/home/aiops/duanky/miniconda3/envs/lora/lib/python3.11/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(

 58%|█████▊    | 2001/3449 [1:34:22<1:10:38,  2.93s/it]
                                                       
{'loss': 1.18, 'learning_rate': 0.00015782449220228144, 'epoch': 0.58}

 58%|█████▊    | 2001/3449 [1:34:22<1:10:38,  2.93s/it]
 58%|█████▊    | 2002/3449 [1:34:24<1:08:48,  2.85s/it]
                                                       
{'loss': 1.2754, 'learning_rate': 0.00015764111597842717, 'epoch': 0.58}

 58%|█████▊    | 2002/3449 [1:34:24<1:08:48,  2.85s/it]
 58%|█████▊    | 2003/3449 [1:34:26<1:04:15,  2.67s/it]
                                                       
{'loss': 1.3271, 'learning_rate': 0.00015745777702925326, 'epoch': 0.58}

 58%|█████▊    | 2003/3449 [1:34:26<1:04:15,  2.67s/it]
 58%|█████▊    | 2004/3449 [1:34:29<1:05:26,  2.72s/it]
                                                       
{'loss': 1.1925, 'learning_rate': 0.00015727447551609303, 'epoch': 0.58}

 58%|█████▊    | 2004/3449 [1:34:29<1:05:26,  2.72s/it]
 58%|█████▊    | 2005/3449 [1:34:32<1:05:08,  2.71s/it]
                                                       
{'loss': 1.2643, 'learning_rate': 0.00015709121160024703, 'epoch': 0.58}

 58%|█████▊    | 2005/3449 [1:34:32<1:05:08,  2.71s/it]
 58%|█████▊    | 2006/3449 [1:34:35<1:06:30,  2.77s/it]
                                                       
{'loss': 1.1895, 'learning_rate': 0.00015690798544298247, 'epoch': 0.58}

 58%|█████▊    | 2006/3449 [1:34:35<1:06:30,  2.77s/it]
 58%|█████▊    | 2007/3449 [1:34:37<1:02:54,  2.62s/it]
                                                       
{'loss': 1.2227, 'learning_rate': 0.00015672479720553342, 'epoch': 0.58}

 58%|█████▊    | 2007/3449 [1:34:37<1:02:54,  2.62s/it]
 58%|█████▊    | 2008/3449 [1:34:40<1:03:47,  2.66s/it]
                                                       
{'loss': 1.2444, 'learning_rate': 0.00015654164704910077, 'epoch': 0.58}

 58%|█████▊    | 2008/3449 [1:34:40<1:03:47,  2.66s/it]
 58%|█████▊    | 2009/3449 [1:34:43<1:06:12,  2.76s/it]
                                                       
{'loss': 1.2285, 'learning_rate': 0.00015635853513485152, 'epoch': 0.58}

 58%|█████▊    | 2009/3449 [1:34:43<1:06:12,  2.76s/it]
 58%|█████▊    | 2010/3449 [1:34:46<1:05:47,  2.74s/it]
                                                       
{'loss': 1.2886, 'learning_rate': 0.00015617546162391944, 'epoch': 0.58}

 58%|█████▊    | 2010/3449 [1:34:46<1:05:47,  2.74s/it]
 58%|█████▊    | 2011/3449 [1:34:48<1:03:11,  2.64s/it]
                                                       
{'loss': 1.2606, 'learning_rate': 0.00015599242667740416, 'epoch': 0.58}

 58%|█████▊    | 2011/3449 [1:34:48<1:03:11,  2.64s/it]
 58%|█████▊    | 2012/3449 [1:34:51<1:03:56,  2.67s/it]
                                                       
{'loss': 1.3832, 'learning_rate': 0.0001558094304563716, 'epoch': 0.58}

 58%|█████▊    | 2012/3449 [1:34:51<1:03:56,  2.67s/it]
 58%|█████▊    | 2013/3449 [1:34:54<1:08:51,  2.88s/it]
                                                       
{'loss': 1.2479, 'learning_rate': 0.00015562647312185353, 'epoch': 0.58}

 58%|█████▊    | 2013/3449 [1:34:54<1:08:51,  2.88s/it]
 58%|█████▊    | 2014/3449 [1:34:58<1:13:49,  3.09s/it]
                                                       
{'loss': 0.9849, 'learning_rate': 0.00015544355483484737, 'epoch': 0.58}

 58%|█████▊    | 2014/3449 [1:34:58<1:13:49,  3.09s/it]
 58%|█████▊    | 2015/3449 [1:35:00<1:09:52,  2.92s/it]
                                                       
{'loss': 1.2859, 'learning_rate': 0.0001552606757563164, 'epoch': 0.58}

 58%|█████▊    | 2015/3449 [1:35:00<1:09:52,  2.92s/it]
 58%|█████▊    | 2016/3449 [1:35:03<1:08:46,  2.88s/it]
                                                       
{'loss': 1.1702, 'learning_rate': 0.00015507783604718932, 'epoch': 0.58}

 58%|█████▊    | 2016/3449 [1:35:03<1:08:46,  2.88s/it]
 58%|█████▊    | 2017/3449 [1:35:06<1:10:49,  2.97s/it]
                                                       
{'loss': 1.1684, 'learning_rate': 0.0001548950358683601, 'epoch': 0.58}

 58%|█████▊    | 2017/3449 [1:35:06<1:10:49,  2.97s/it]
 59%|█████▊    | 2018/3449 [1:35:09<1:09:08,  2.90s/it]
                                                       
{'loss': 1.2288, 'learning_rate': 0.00015471227538068797, 'epoch': 0.59}

 59%|█████▊    | 2018/3449 [1:35:09<1:09:08,  2.90s/it]
 59%|█████▊    | 2019/3449 [1:35:12<1:12:29,  3.04s/it]
                                                       
{'loss': 1.2113, 'learning_rate': 0.00015452955474499737, 'epoch': 0.59}

 59%|█████▊    | 2019/3449 [1:35:12<1:12:29,  3.04s/it]
 59%|█████▊    | 2020/3449 [1:35:15<1:10:49,  2.97s/it]
                                                       
{'loss': 1.1303, 'learning_rate': 0.00015434687412207746, 'epoch': 0.59}

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{'loss': 1.3073, 'learning_rate': 0.00015416423367268223, 'epoch': 0.59}

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{'loss': 1.2214, 'learning_rate': 0.00015398163355753052, 'epoch': 0.59}

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{'loss': 1.2013, 'learning_rate': 0.00015379907393730542, 'epoch': 0.59}

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{'loss': 1.0688, 'learning_rate': 0.00015361655497265456, 'epoch': 0.59}

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{'loss': 1.1376, 'learning_rate': 0.00015343407682418962, 'epoch': 0.59}

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{'loss': 1.2122, 'learning_rate': 0.00015325163965248652, 'epoch': 0.59}

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{'loss': 1.236, 'learning_rate': 0.00015306924361808516, 'epoch': 0.59}

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{'loss': 1.0998, 'learning_rate': 0.00014220681187832328, 'epoch': 0.61}

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{'loss': 1.2991, 'learning_rate': 0.00014202722727868272, 'epoch': 0.61}

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{'loss': 1.2619, 'learning_rate': 0.00014184769369352524, 'epoch': 0.61}

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{'loss': 1.2346, 'learning_rate': 0.00014166821128083559, 'epoch': 0.61}

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{'loss': 1.3648, 'learning_rate': 0.0001414887801985536, 'epoch': 0.61}

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{'loss': 1.2671, 'learning_rate': 0.00014130940060457357, 'epoch': 0.61}

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{'loss': 1.287, 'learning_rate': 2.042709994289107e-05, 'epoch': 0.86}

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{'loss': 1.2926, 'learning_rate': 2.034457789316524e-05, 'epoch': 0.86}

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{'loss': 1.1133, 'learning_rate': 2.0262213935386232e-05, 'epoch': 0.86}

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{'loss': 1.3774, 'learning_rate': 2.0180008142032092e-05, 'epoch': 0.86}

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{'loss': 1.1204, 'learning_rate': 2.0097960585441645e-05, 'epoch': 0.86}

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{'loss': 1.1569, 'learning_rate': 2.0016071337814558e-05, 'epoch': 0.86}

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{'loss': 1.1471, 'learning_rate': 1.993434047121123e-05, 'epoch': 0.86}

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{'loss': 1.081, 'learning_rate': 1.9852768057552585e-05, 'epoch': 0.86}

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{'loss': 1.2108, 'learning_rate': 1.9771354168620125e-05, 'epoch': 0.86}

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{'loss': 1.2698, 'learning_rate': 1.9690098876055953e-05, 'epoch': 0.86}

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{'loss': 1.1888, 'learning_rate': 1.9609002251362486e-05, 'epoch': 0.86}

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{'loss': 1.1195, 'learning_rate': 1.95280643659026e-05, 'epoch': 0.86}

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{'loss': 1.2994, 'learning_rate': 1.9447285290899474e-05, 'epoch': 0.86}

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{'loss': 1.2338, 'learning_rate': 1.9366665097436497e-05, 'epoch': 0.86}

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{'loss': 1.177, 'learning_rate': 1.928620385645734e-05, 'epoch': 0.86}

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{'loss': 1.2411, 'learning_rate': 1.9205901638765612e-05, 'epoch': 0.86}

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{'loss': 1.1876, 'learning_rate': 1.9125758515025205e-05, 'epoch': 0.86}

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{'loss': 1.2754, 'learning_rate': 1.904577455575991e-05, 'epoch': 0.86}

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{'loss': 1.1749, 'learning_rate': 1.8965949831353403e-05, 'epoch': 0.86}

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{'loss': 1.1482, 'learning_rate': 1.8886284412049337e-05, 'epoch': 0.86}

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{'loss': 1.1196, 'learning_rate': 1.8806778367951218e-05, 'epoch': 0.87}

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{'loss': 1.3412, 'learning_rate': 1.8727431769022098e-05, 'epoch': 0.87}

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{'loss': 1.2215, 'learning_rate': 1.8648244685084858e-05, 'epoch': 0.87}

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{'loss': 1.1714, 'learning_rate': 1.8569217185822164e-05, 'epoch': 0.87}

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{'loss': 1.2181, 'learning_rate': 1.8490349340775916e-05, 'epoch': 0.87}

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{'loss': 1.1393, 'learning_rate': 1.8411641219347775e-05, 'epoch': 0.87}

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{'loss': 1.3228, 'learning_rate': 1.8333092890798788e-05, 'epoch': 0.87}

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{'loss': 1.1247, 'learning_rate': 1.8254704424249324e-05, 'epoch': 0.87}

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{'loss': 1.3653, 'learning_rate': 1.817647588867919e-05, 'epoch': 0.87}

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{'loss': 1.2809, 'learning_rate': 1.809840735292736e-05, 'epoch': 0.87}

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{'loss': 1.0852, 'learning_rate': 1.802049888569204e-05, 'epoch': 0.87}

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{'loss': 1.1379, 'learning_rate': 1.794275055553065e-05, 'epoch': 0.87}

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{'loss': 1.2159, 'learning_rate': 1.7865162430859496e-05, 'epoch': 0.87}

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{'loss': 1.0354, 'learning_rate': 1.7787734579954195e-05, 'epoch': 0.87}

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{'loss': 1.3856, 'learning_rate': 1.7710467070949142e-05, 'epoch': 0.87}

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{'loss': 1.1133, 'learning_rate': 1.763335997183757e-05, 'epoch': 0.87}

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{'loss': 1.2981, 'learning_rate': 1.75564133504718e-05, 'epoch': 0.87}

 87%|████████▋ | 3000/3449 [2:21:29<21:15,  2.84s/it]/home/aiops/duanky/miniconda3/envs/lora/lib/python3.11/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(

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{'loss': 1.2427, 'learning_rate': 1.7479627274562672e-05, 'epoch': 0.87}

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{'loss': 1.1127, 'learning_rate': 1.7403001811679932e-05, 'epoch': 0.87}

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{'loss': 1.2479, 'learning_rate': 1.7326537029251933e-05, 'epoch': 0.87}

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{'loss': 1.1347, 'learning_rate': 1.7250232994565606e-05, 'epoch': 0.87}

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{'loss': 1.218, 'learning_rate': 1.7174089774766443e-05, 'epoch': 0.87}

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{'loss': 1.1078, 'learning_rate': 1.709810743685847e-05, 'epoch': 0.87}

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{'loss': 1.3854, 'learning_rate': 1.7022286047704082e-05, 'epoch': 0.87}

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{'loss': 1.243, 'learning_rate': 1.6946625674024052e-05, 'epoch': 0.87}

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{'loss': 1.1764, 'learning_rate': 1.6871126382397516e-05, 'epoch': 0.87}

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{'loss': 1.1269, 'learning_rate': 1.679578823926178e-05, 'epoch': 0.87}

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{'loss': 1.2676, 'learning_rate': 1.672061131091245e-05, 'epoch': 0.87}

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{'loss': 1.1869, 'learning_rate': 1.6645595663503122e-05, 'epoch': 0.87}

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{'loss': 1.0474, 'learning_rate': 1.657074136304555e-05, 'epoch': 0.87}

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{'loss': 1.1431, 'learning_rate': 1.6496048475409643e-05, 'epoch': 0.87}

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{'loss': 1.0896, 'learning_rate': 1.6421517066322976e-05, 'epoch': 0.87}

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{'loss': 1.1337, 'learning_rate': 1.6347147201371228e-05, 'epoch': 0.87}

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{'loss': 1.1946, 'learning_rate': 1.627293894599797e-05, 'epoch': 0.87}

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{'loss': 1.1951, 'learning_rate': 1.6198892365504403e-05, 'epoch': 0.87}

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{'loss': 1.2758, 'learning_rate': 1.6125007525049508e-05, 'epoch': 0.88}

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{'loss': 1.1122, 'learning_rate': 1.605128448965001e-05, 'epoch': 0.88}

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{'loss': 1.2284, 'learning_rate': 1.597772332418017e-05, 'epoch': 0.88}

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{'loss': 1.232, 'learning_rate': 1.590432409337186e-05, 'epoch': 0.88}

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{'loss': 1.2455, 'learning_rate': 1.5831086861814404e-05, 'epoch': 0.88}

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{'loss': 1.2027, 'learning_rate': 1.575801169395461e-05, 'epoch': 0.88}

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{'loss': 1.3046, 'learning_rate': 1.568509865409673e-05, 'epoch': 0.88}

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{'loss': 1.1795, 'learning_rate': 1.5612347806402127e-05, 'epoch': 0.88}

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{'loss': 1.3274, 'learning_rate': 1.5539759214889725e-05, 'epoch': 0.88}

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{'loss': 1.1827, 'learning_rate': 1.5467332943435543e-05, 'epoch': 0.88}

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{'loss': 1.1546, 'learning_rate': 1.539506905577266e-05, 'epoch': 0.88}

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{'loss': 1.2797, 'learning_rate': 1.5322967615491367e-05, 'epoch': 0.88}

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{'loss': 1.1132, 'learning_rate': 1.5251028686039115e-05, 'epoch': 0.88}

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{'loss': 1.2323, 'learning_rate': 1.5179252330720107e-05, 'epoch': 0.88}

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{'loss': 1.1206, 'learning_rate': 1.5107638612695619e-05, 'epoch': 0.88}

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{'loss': 1.2563, 'learning_rate': 1.5036187594983885e-05, 'epoch': 0.88}

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{'train_runtime': 9769.0231, 'train_samples_per_second': 11.299, 'train_steps_per_second': 0.353, 'train_loss': 1.2677869534416453, 'epoch': 1.0}

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wandb: 
wandb: Run history:
wandb:                    train/epoch ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▄▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███
wandb:              train/global_step ▁▁▁▂▂▂▂▂▂▃▃▃▃▃▄▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███
wandb:            train/learning_rate ▃███████▇▇▇▇▇▆▆▆▆▅▅▅▅▄▄▄▃▃▃▃▂▂▂▂▂▁▁▁▁▁▁▁
wandb:                     train/loss █▆▅▆▅▇▄▆▄▆▄██▆▆▂▆▄▄▄▄▄▆▃▄▃▄▅▃▂▄▃▅▃▅▂▁▄▄▃
wandb:               train/total_flos ▁
wandb:               train/train_loss ▁
wandb:            train/train_runtime ▁
wandb: train/train_samples_per_second ▁
wandb:   train/train_steps_per_second ▁
wandb: 
wandb: Run summary:
wandb:                    train/epoch 1.0
wandb:              train/global_step 3449
wandb:            train/learning_rate 0.0
wandb:                     train/loss 1.0618
wandb:               train/total_flos 1.0345695487385928e+18
wandb:               train/train_loss 1.26779
wandb:            train/train_runtime 9769.0231
wandb: train/train_samples_per_second 11.299
wandb:   train/train_steps_per_second 0.353
wandb: 
wandb: 🚀 View run belle_dolphine-p13 at: https://wandb.ai/nus_keyu/lora-moe/runs/rpu8pnl2
wandb: Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
wandb: Find logs at: ./wandb/run-20231229_120011-rpu8pnl2/logs