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05/10/2023 09:41:07 - WARNING - __main__ - Process rank: 0, device: cuda:0, n_gpu: 2distributed training: True, 16-bits training: True
05/10/2023 09:41:07 - INFO - __main__ - Training/evaluation parameters Seq2SeqTrainingArguments(
_n_gpu=2,
adafactor=False,
adam_beta1=0.9,
adam_beta2=0.999,
adam_epsilon=1e-08,
auto_find_batch_size=False,
bf16=False,
bf16_full_eval=False,
data_seed=None,
dataloader_drop_last=False,
dataloader_num_workers=0,
dataloader_pin_memory=True,
ddp_backend=None,
ddp_bucket_cap_mb=None,
ddp_find_unused_parameters=None,
ddp_timeout=1800,
debug=[],
deepspeed=None,
disable_tqdm=False,
do_eval=True,
do_predict=False,
do_train=True,
eval_accumulation_steps=None,
eval_delay=0,
eval_steps=1000,
evaluation_strategy=steps,
fp16=True,
fp16_backend=auto,
fp16_full_eval=False,
fp16_opt_level=O1,
fsdp=[],
fsdp_config={'fsdp_min_num_params': 0, 'xla': False, 'xla_fsdp_grad_ckpt': False},
fsdp_min_num_params=0,
fsdp_transformer_layer_cls_to_wrap=None,
full_determinism=False,
generation_config=None,
generation_max_length=225,
generation_num_beams=None,
gradient_accumulation_steps=2,
gradient_checkpointing=True,
greater_is_better=False,
group_by_length=False,
half_precision_backend=auto,
hub_model_id=None,
hub_private_repo=False,
hub_strategy=every_save,
hub_token=<HUB_TOKEN>,
ignore_data_skip=False,
include_inputs_for_metrics=False,
jit_mode_eval=False,
label_names=None,
label_smoothing_factor=0.0,
learning_rate=1e-05,
length_column_name=input_length,
load_best_model_at_end=True,
local_rank=0,
log_level=passive,
log_level_replica=warning,
log_on_each_node=True,
logging_dir=./runs/May10_09-41-06_crimv3mgpu016,
logging_first_step=False,
logging_nan_inf_filter=True,
logging_steps=25,
logging_strategy=steps,
lr_scheduler_type=linear,
max_grad_norm=1.0,
max_steps=5000,
metric_for_best_model=wer,
mp_parameters=,
no_cuda=False,
num_train_epochs=3.0,
optim=adamw_hf,
optim_args=None,
output_dir=./,
overwrite_output_dir=True,
past_index=-1,
per_device_eval_batch_size=32,
per_device_train_batch_size=32,
predict_with_generate=True,
prediction_loss_only=False,
push_to_hub=True,
push_to_hub_model_id=None,
push_to_hub_organization=None,
push_to_hub_token=<PUSH_TO_HUB_TOKEN>,
ray_scope=last,
remove_unused_columns=True,
report_to=['wandb'],
resume_from_checkpoint=None,
run_name=./,
save_on_each_node=False,
save_safetensors=False,
save_steps=1000,
save_strategy=steps,
save_total_limit=None,
seed=42,
sharded_ddp=[],
skip_memory_metrics=True,
sortish_sampler=False,
tf32=None,
torch_compile=False,
torch_compile_backend=None,
torch_compile_mode=None,
torchdynamo=None,
tpu_metrics_debug=False,
tpu_num_cores=None,
use_ipex=False,
use_legacy_prediction_loop=False,
use_mps_device=False,
warmup_ratio=0.0,
warmup_steps=500,
weight_decay=0.0,
xpu_backend=None,
)
05/10/2023 09:41:07 - INFO - __main__ - Training/evaluation parameters Seq2SeqTrainingArguments(
_n_gpu=2,
adafactor=False,
adam_beta1=0.9,
adam_beta2=0.999,
adam_epsilon=1e-08,
auto_find_batch_size=False,
bf16=False,
bf16_full_eval=False,
data_seed=None,
dataloader_drop_last=False,
dataloader_num_workers=0,
dataloader_pin_memory=True,
ddp_backend=None,
ddp_bucket_cap_mb=None,
ddp_find_unused_parameters=None,
ddp_timeout=1800,
debug=[],
deepspeed=None,
disable_tqdm=False,
do_eval=True,
do_predict=False,
do_train=True,
eval_accumulation_steps=None,
eval_delay=0,
eval_steps=1000,
evaluation_strategy=steps,
fp16=True,
fp16_backend=auto,
fp16_full_eval=False,
fp16_opt_level=O1,
fsdp=[],
fsdp_config={'fsdp_min_num_params': 0, 'xla': False, 'xla_fsdp_grad_ckpt': False},
fsdp_min_num_params=0,
fsdp_transformer_layer_cls_to_wrap=None,
full_determinism=False,
generation_config=None,
generation_max_length=225,
generation_num_beams=None,
gradient_accumulation_steps=2,
gradient_checkpointing=True,
greater_is_better=False,
group_by_length=False,
half_precision_backend=auto,
hub_model_id=None,
hub_private_repo=False,
hub_strategy=every_save,
hub_token=<HUB_TOKEN>,
ignore_data_skip=False,
include_inputs_for_metrics=False,
jit_mode_eval=False,
label_names=None,
label_smoothing_factor=0.0,
learning_rate=1e-05,
length_column_name=input_length,
load_best_model_at_end=True,
local_rank=0,
log_level=passive,
log_level_replica=warning,
log_on_each_node=True,
logging_dir=./runs/May10_09-41-06_crimv3mgpu016,
logging_first_step=False,
logging_nan_inf_filter=True,
logging_steps=25,
logging_strategy=steps,
lr_scheduler_type=linear,
max_grad_norm=1.0,
max_steps=5000,
metric_for_best_model=wer,
mp_parameters=,
no_cuda=False,
num_train_epochs=3.0,
optim=adamw_hf,
optim_args=None,
output_dir=./,
overwrite_output_dir=True,
past_index=-1,
per_device_eval_batch_size=32,
per_device_train_batch_size=32,
predict_with_generate=True,
prediction_loss_only=False,
push_to_hub=True,
push_to_hub_model_id=None,
push_to_hub_organization=None,
push_to_hub_token=<PUSH_TO_HUB_TOKEN>,
ray_scope=last,
remove_unused_columns=True,
report_to=['wandb'],
resume_from_checkpoint=None,
run_name=./,
save_on_each_node=False,
save_safetensors=False,
save_steps=1000,
save_strategy=steps,
save_total_limit=None,
seed=42,
sharded_ddp=[],
skip_memory_metrics=True,
sortish_sampler=False,
tf32=None,
torch_compile=False,
torch_compile_backend=None,
torch_compile_mode=None,
torchdynamo=None,
tpu_metrics_debug=False,
tpu_num_cores=None,
use_ipex=False,
use_legacy_prediction_loop=False,
use_mps_device=False,
warmup_ratio=0.0,
warmup_steps=500,
weight_decay=0.0,
xpu_backend=None,
)
[INFO|configuration_utils.py:669] 2023-05-10 09:41:19,641 >> loading configuration file config.json from cache at /home/local/QCRI/dizham/.cache/huggingface/hub/models--openai--whisper-small/snapshots/f6744499d1eba717bcf4d6be735e3d386ffb60ad/config.json
[INFO|configuration_utils.py:725] 2023-05-10 09:41:19,653 >> Model config WhisperConfig {
"_name_or_path": "openai/whisper-small",
"activation_dropout": 0.0,
"activation_function": "gelu",
"apply_spec_augment": false,
"architectures": [
"WhisperForConditionalGeneration"
],
"attention_dropout": 0.0,
"begin_suppress_tokens": [
220,
50257
],
"bos_token_id": 50257,
"classifier_proj_size": 256,
"d_model": 768,
"decoder_attention_heads": 12,
"decoder_ffn_dim": 3072,
"decoder_layerdrop": 0.0,
"decoder_layers": 12,
"decoder_start_token_id": 50258,
"dropout": 0.0,
"encoder_attention_heads": 12,
"encoder_ffn_dim": 3072,
"encoder_layerdrop": 0.0,
"encoder_layers": 12,
"eos_token_id": 50257,
"forced_decoder_ids": [
[
1,
50259
],
[
2,
50359
],
[
3,
50363
]
],
"init_std": 0.02,
"is_encoder_decoder": true,
"mask_feature_length": 10,
"mask_feature_min_masks": 0,
"mask_feature_prob": 0.0,
"mask_time_length": 10,
"mask_time_min_masks": 2,
"mask_time_prob": 0.05,
"max_length": 448,
"max_source_positions": 1500,
"max_target_positions": 448,
"model_type": "whisper",
"num_hidden_layers": 12,
"num_mel_bins": 80,
"pad_token_id": 50257,
"scale_embedding": false,
"suppress_tokens": [
1,
2,
7,
8,
9,
10,
14,
25,
26,
27,
28,
29,
31,
58,
59,
60,
61,
62,
63,
90,
91,
92,
93,
359,
503,
522,
542,
873,
893,
902,
918,
922,
931,
1350,
1853,
1982,
2460,
2627,
3246,
3253,
3268,
3536,
3846,
3961,
4183,
4667,
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7273,
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9383,
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12562,
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14157,
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15265,
15618,
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18362,
18956,
20075,
21675,
22520,
26130,
26161,
26435,
28279,
29464,
31650,
32302,
32470,
36865,
42863,
47425,
49870,
50254,
50258,
50360,
50361,
50362
],
"torch_dtype": "float32",
"transformers_version": "4.29.0.dev0",
"use_cache": true,
"use_weighted_layer_sum": false,
"vocab_size": 51865
}
[INFO|feature_extraction_utils.py:469] 2023-05-10 09:41:19,843 >> loading configuration file preprocessor_config.json from cache at /home/local/QCRI/dizham/.cache/huggingface/hub/models--openai--whisper-small/snapshots/f6744499d1eba717bcf4d6be735e3d386ffb60ad/preprocessor_config.json
[INFO|feature_extraction_utils.py:511] 2023-05-10 09:41:19,849 >> Feature extractor WhisperFeatureExtractor {
"chunk_length": 30,
"feature_extractor_type": "WhisperFeatureExtractor",
"feature_size": 80,
"hop_length": 160,
"n_fft": 400,
"n_samples": 480000,
"nb_max_frames": 3000,
"padding_side": "right",
"padding_value": 0.0,
"processor_class": "WhisperProcessor",
"return_attention_mask": false,
"sampling_rate": 16000
}
[INFO|tokenization_utils_base.py:1810] 2023-05-10 09:41:20,054 >> loading file vocab.json from cache at /home/local/QCRI/dizham/.cache/huggingface/hub/models--openai--whisper-small/snapshots/f6744499d1eba717bcf4d6be735e3d386ffb60ad/vocab.json
[INFO|tokenization_utils_base.py:1810] 2023-05-10 09:41:20,054 >> loading file tokenizer.json from cache at /home/local/QCRI/dizham/.cache/huggingface/hub/models--openai--whisper-small/snapshots/f6744499d1eba717bcf4d6be735e3d386ffb60ad/tokenizer.json
[INFO|tokenization_utils_base.py:1810] 2023-05-10 09:41:20,054 >> loading file merges.txt from cache at /home/local/QCRI/dizham/.cache/huggingface/hub/models--openai--whisper-small/snapshots/f6744499d1eba717bcf4d6be735e3d386ffb60ad/merges.txt
[INFO|tokenization_utils_base.py:1810] 2023-05-10 09:41:20,054 >> loading file normalizer.json from cache at /home/local/QCRI/dizham/.cache/huggingface/hub/models--openai--whisper-small/snapshots/f6744499d1eba717bcf4d6be735e3d386ffb60ad/normalizer.json
[INFO|tokenization_utils_base.py:1810] 2023-05-10 09:41:20,054 >> loading file added_tokens.json from cache at /home/local/QCRI/dizham/.cache/huggingface/hub/models--openai--whisper-small/snapshots/f6744499d1eba717bcf4d6be735e3d386ffb60ad/added_tokens.json
[INFO|tokenization_utils_base.py:1810] 2023-05-10 09:41:20,054 >> loading file special_tokens_map.json from cache at /home/local/QCRI/dizham/.cache/huggingface/hub/models--openai--whisper-small/snapshots/f6744499d1eba717bcf4d6be735e3d386ffb60ad/special_tokens_map.json
[INFO|tokenization_utils_base.py:1810] 2023-05-10 09:41:20,054 >> loading file tokenizer_config.json from cache at /home/local/QCRI/dizham/.cache/huggingface/hub/models--openai--whisper-small/snapshots/f6744499d1eba717bcf4d6be735e3d386ffb60ad/tokenizer_config.json
[INFO|modeling_utils.py:2542] 2023-05-10 09:41:20,144 >> loading weights file pytorch_model.bin from cache at /home/local/QCRI/dizham/.cache/huggingface/hub/models--openai--whisper-small/snapshots/f6744499d1eba717bcf4d6be735e3d386ffb60ad/pytorch_model.bin
[INFO|configuration_utils.py:577] 2023-05-10 09:41:20,754 >> Generate config GenerationConfig {
"_from_model_config": true,
"begin_suppress_tokens": [
220,
50257
],
"bos_token_id": 50257,
"decoder_start_token_id": 50258,
"eos_token_id": 50257,
"max_length": 448,
"pad_token_id": 50257,
"transformers_version": "4.29.0.dev0",
"use_cache": false
}
[INFO|modeling_utils.py:3211] 2023-05-10 09:41:23,296 >> All model checkpoint weights were used when initializing WhisperForConditionalGeneration.
[INFO|modeling_utils.py:3219] 2023-05-10 09:41:23,296 >> All the weights of WhisperForConditionalGeneration were initialized from the model checkpoint at openai/whisper-small.
If your task is similar to the task the model of the checkpoint was trained on, you can already use WhisperForConditionalGeneration for predictions without further training.
[INFO|configuration_utils.py:539] 2023-05-10 09:41:23,501 >> loading configuration file generation_config.json from cache at /home/local/QCRI/dizham/.cache/huggingface/hub/models--openai--whisper-small/snapshots/f6744499d1eba717bcf4d6be735e3d386ffb60ad/generation_config.json
[INFO|configuration_utils.py:577] 2023-05-10 09:41:23,502 >> Generate config GenerationConfig {
"begin_suppress_tokens": [
220,
50257
],
"bos_token_id": 50257,
"decoder_start_token_id": 50258,
"eos_token_id": 50257,
"forced_decoder_ids": [
[
1,
null
],
[
2,
50359
]
],
"is_multilingual": true,
"lang_to_id": {
"<|af|>": 50327,
"<|am|>": 50334,
"<|ar|>": 50272,
"<|as|>": 50350,
"<|az|>": 50304,
"<|ba|>": 50355,
"<|be|>": 50330,
"<|bg|>": 50292,
"<|bn|>": 50302,
"<|bo|>": 50347,
"<|br|>": 50309,
"<|bs|>": 50315,
"<|ca|>": 50270,
"<|cs|>": 50283,
"<|cy|>": 50297,
"<|da|>": 50285,
"<|de|>": 50261,
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"<|en|>": 50259,
"<|es|>": 50262,
"<|et|>": 50307,
"<|eu|>": 50310,
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"<|fr|>": 50265,
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"<|gu|>": 50333,
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"<|id|>": 50275,
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"<|vi|>": 50278,
"<|yi|>": 50335,
"<|yo|>": 50325,
"<|zh|>": 50260
},
"max_initial_timestamp_index": 1,
"max_length": 448,
"no_timestamps_token_id": 50363,
"pad_token_id": 50257,
"return_timestamps": false,
"suppress_tokens": [
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22520,
26130,
26161,
26435,
28279,
29464,
31650,
32302,
32470,
36865,
42863,
47425,
49870,
50254,
50258,
50358,
50359,
50360,
50361,
50362
],
"task_to_id": {
"transcribe": 50359,
"translate": 50358
},
"transformers_version": "4.29.0.dev0"
}
[INFO|feature_extraction_utils.py:369] 2023-05-10 09:41:24,661 >> Feature extractor saved in ./preprocessor_config.json
[INFO|tokenization_utils_base.py:2181] 2023-05-10 09:41:24,666 >> tokenizer config file saved in ./tokenizer_config.json
[INFO|tokenization_utils_base.py:2188] 2023-05-10 09:41:24,671 >> Special tokens file saved in ./special_tokens_map.json
[INFO|configuration_utils.py:458] 2023-05-10 09:41:24,826 >> Configuration saved in ./config.json
[INFO|image_processing_utils.py:307] 2023-05-10 09:41:24,827 >> loading configuration file ./preprocessor_config.json
[INFO|feature_extraction_utils.py:467] 2023-05-10 09:41:24,834 >> loading configuration file ./preprocessor_config.json
[INFO|feature_extraction_utils.py:511] 2023-05-10 09:41:24,835 >> Feature extractor WhisperFeatureExtractor {
"chunk_length": 30,
"feature_extractor_type": "WhisperFeatureExtractor",
"feature_size": 80,
"hop_length": 160,
"n_fft": 400,
"n_samples": 480000,
"nb_max_frames": 3000,
"padding_side": "right",
"padding_value": 0.0,
"processor_class": "WhisperProcessor",
"return_attention_mask": false,
"sampling_rate": 16000
}
[INFO|tokenization_utils_base.py:1808] 2023-05-10 09:41:24,836 >> loading file vocab.json
[INFO|tokenization_utils_base.py:1808] 2023-05-10 09:41:24,836 >> loading file tokenizer.json
[INFO|tokenization_utils_base.py:1808] 2023-05-10 09:41:24,836 >> loading file merges.txt
[INFO|tokenization_utils_base.py:1808] 2023-05-10 09:41:24,836 >> loading file normalizer.json
[INFO|tokenization_utils_base.py:1808] 2023-05-10 09:41:24,836 >> loading file added_tokens.json
[INFO|tokenization_utils_base.py:1808] 2023-05-10 09:41:24,836 >> loading file special_tokens_map.json
[INFO|tokenization_utils_base.py:1808] 2023-05-10 09:41:24,836 >> loading file tokenizer_config.json
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|startoftranscript|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|en|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|zh|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|de|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|es|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|ru|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|ko|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|fr|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|ja|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|pt|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|tr|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|pl|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|ca|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|nl|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|ar|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|sv|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|it|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|id|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|hi|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|fi|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|vi|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|he|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|uk|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|el|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|ms|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|cs|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|ro|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|da|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|hu|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|ta|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|no|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <|th|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|ur|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|hr|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|bg|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|lt|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|la|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|mi|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|ml|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|cy|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|sk|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|te|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|fa|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|lv|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|bn|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|sr|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|az|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|sl|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|kn|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|et|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|mk|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|br|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|eu|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|is|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|hy|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|ne|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|mn|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|bs|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|kk|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|sq|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|sw|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|gl|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|mr|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|pa|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|si|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|km|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|sn|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|yo|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|so|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|af|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|oc|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|ka|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|be|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <|tg|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|sd|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|gu|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|am|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|yi|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|lo|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|uz|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|fo|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|ht|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|ps|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|tk|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|nn|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|mt|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|sa|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|lb|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|my|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|bo|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|tl|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|mg|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|as|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|tt|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|haw|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|ln|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|ha|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|ba|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|jw|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|su|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|translate|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|transcribe|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|startoflm|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|startofprev|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|nocaptions|> to the vocabulary
[INFO|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <|notimestamps|> to the vocabulary
/home/local/QCRI/dizham/kanari/whisper/whisper-small-es/./ is already a clone of https://huggingface.co/danielizham/whisper-small-es. Make sure you pull the latest changes with `repo.git_pull()`.
05/10/2023 09:41:27 - WARNING - huggingface_hub.repository - /home/local/QCRI/dizham/kanari/whisper/whisper-small-es/./ is already a clone of https://huggingface.co/danielizham/whisper-small-es. Make sure you pull the latest changes with `repo.git_pull()`.
[INFO|trainer.py:565] 2023-05-10 09:41:30,128 >> max_steps is given, it will override any value given in num_train_epochs
[INFO|trainer.py:622] 2023-05-10 09:41:30,129 >> Using cuda_amp half precision backend
/home/local/QCRI/dizham/miniconda3/envs/whisper/lib/python3.9/site-packages/transformers/optimization.py:407: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning
warnings.warn(
[INFO|trainer.py:1771] 2023-05-10 09:41:30,142 >> ***** Running training *****
[INFO|trainer.py:1772] 2023-05-10 09:41:30,142 >> Num examples = 640,000
[INFO|trainer.py:1773] 2023-05-10 09:41:30,142 >> Num Epochs = 9,223,372,036,854,775,807
[INFO|trainer.py:1774] 2023-05-10 09:41:30,142 >> Instantaneous batch size per device = 32
[INFO|trainer.py:1775] 2023-05-10 09:41:30,142 >> Total train batch size (w. parallel, distributed & accumulation) = 128
[INFO|trainer.py:1776] 2023-05-10 09:41:30,142 >> Gradient Accumulation steps = 2
[INFO|trainer.py:1777] 2023-05-10 09:41:30,142 >> Total optimization steps = 5,000
[INFO|trainer.py:1778] 2023-05-10 09:41:30,143 >> Number of trainable parameters = 241,734,912
[INFO|integrations.py:720] 2023-05-10 09:41:30,144 >> Automatic Weights & Biases logging enabled, to disable set os.environ["WANDB_DISABLED"] = "true"
wandb: Currently logged in as: danielizham. Use `wandb login --relogin` to force relogin
wandb: Tracking run with wandb version 0.15.2
wandb: Run data is saved locally in /home/local/QCRI/dizham/kanari/whisper/whisper-small-es/wandb/run-20230510_094132-lvsln7ks
wandb: Run `wandb offline` to turn off syncing.
wandb: Syncing run astral-silence-4
wandb: ⭐️ View project at https://wandb.ai/danielizham/huggingface
wandb: 🚀 View run at https://wandb.ai/danielizham/huggingface/runs/lvsln7ks
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[INFO|trainer_utils.py:693] 2023-05-10 09:43:41,176 >> The following columns in the training set don't have a corresponding argument in `WhisperForConditionalGeneration.forward` and have been ignored: input_length. If input_length are not expected by `WhisperForConditionalGeneration.forward`, you can safely ignore this message.
/home/local/QCRI/dizham/miniconda3/envs/whisper/lib/python3.9/site-packages/torch/nn/parallel/_functions.py:68: UserWarning: Was asked to gather along dimension 0, but all input tensors were scalars; will instead unsqueeze and return a vector.
warnings.warn('Was asked to gather along dimension 0, but all '
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5%|▍ | 242/5000 [1:58:41<21:36:39, 16.35s/it]{'loss': 1.0543, 'learning_rate': 4.800000000000001e-07, 'epoch': 0.01}
{'loss': 0.8847, 'learning_rate': 9.800000000000001e-07, 'epoch': 0.01}
{'loss': 0.54, 'learning_rate': 1.48e-06, 'epoch': 0.01}
{'loss': 0.304, 'learning_rate': 1.98e-06, 'epoch': 0.02}
{'loss': 0.2861, 'learning_rate': 2.4800000000000004e-06, 'epoch': 0.03}
{'loss': 0.2395, 'learning_rate': 2.9800000000000003e-06, 'epoch': 0.03}
{'loss': 0.2282, 'learning_rate': 3.48e-06, 'epoch': 0.04}
{'loss': 0.2209, 'learning_rate': 3.980000000000001e-06, 'epoch': 0.04}
{'loss': 0.2299, 'learning_rate': 4.48e-06, 'epoch': 0.04}
Reading metadata...: 0it [00:00, ?it/s][A
Reading metadata...: 1it [00:00, 1.28it/s][A
Reading metadata...: 14726it [00:00, 22755.29it/s][A
Reading metadata...: 23388it [00:03, 6340.58it/s] [A
Reading metadata...: 37933it [00:03, 12680.17it/s][A
Reading metadata...: 46618it [00:06, 6782.81it/s] [A
Reading metadata...: 59039it [00:06, 9618.95it/s][A
Reading metadata...: 72546it [00:06, 14763.51it/s][A
Reading metadata...: 80136it [00:06, 16119.07it/s][A
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Reading metadata...: 102171it [00:15, 3763.63it/s][A
Reading metadata...: 114047it [00:15, 5268.91it/s][A
Reading metadata...: 127993it [00:15, 8041.86it/s][A
Reading metadata...: 135601it [00:15, 9277.73it/s][A
Reading metadata...: 149664it [00:23, 3971.36it/s][A
Reading metadata...: 164498it [00:23, 6070.15it/s][A
Reading metadata...: 171902it [00:23, 6887.15it/s][A
Reading metadata...: 184380it [00:24, 9253.56it/s][A
Reading metadata...: 199395it [00:24, 13975.77it/s][A
Reading metadata...: 207317it [00:24, 15201.63it/s][A
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Reading metadata...: 229844it [00:24, 23238.20it/s][A
Reading metadata...: 230467it [00:24, 9256.50it/s]
Reading metadata...: 0it [00:00, ?it/s][A
Reading metadata...: 1it [00:00, 3.85it/s][A
Reading metadata...: 15233it [00:00, 54060.21it/s][A
Reading metadata...: 15520it [00:00, 42867.71it/s]
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10%|▉ | 485/5000 [3:56:13<18:50:40, 15.03s/it]{'loss': 0.2867, 'learning_rate': 4.980000000000001e-06, 'epoch': 1.0}
{'loss': 0.3646, 'learning_rate': 5.480000000000001e-06, 'epoch': 1.01}
{'loss': 0.3278, 'learning_rate': 5.98e-06, 'epoch': 1.01}
{'loss': 0.3748, 'learning_rate': 6.480000000000001e-06, 'epoch': 1.02}
{'loss': 0.2737, 'learning_rate': 6.98e-06, 'epoch': 1.02}
{'loss': 0.2653, 'learning_rate': 7.48e-06, 'epoch': 1.03}
{'loss': 0.2596, 'learning_rate': 7.980000000000002e-06, 'epoch': 1.03}
{'loss': 0.2665, 'learning_rate': 8.48e-06, 'epoch': 1.04}
{'loss': 0.2598, 'learning_rate': 8.98e-06, 'epoch': 1.04}
{'loss': 0.242, 'learning_rate': 9.48e-06, 'epoch': 1.05}
Reading metadata...: 0it [00:00, ?it/s][A
Reading metadata...: 1it [00:01, 1.04s/it][A
Reading metadata...: 15751it [00:01, 19095.71it/s][A
Reading metadata...: 25016it [00:01, 16623.79it/s][A
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Reading metadata...: 49475it [00:02, 29075.84it/s][A
Reading metadata...: 59039it [00:02, 27352.30it/s][A
Reading metadata...: 73815it [00:02, 41033.71it/s][A
Reading metadata...: 82286it [00:05, 11264.53it/s][A
Reading metadata...: 96058it [00:13, 3486.35it/s] [A
Reading metadata...: 110587it [00:13, 5350.06it/s][A
Reading metadata...: 117905it [00:15, 5480.20it/s][A
Reading metadata...: 132000it [00:16, 6898.25it/s][A
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Reading metadata...: 153083it [00:16, 11213.31it/s][A
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Reading metadata...: 184380it [00:18, 14560.00it/s][A
Reading metadata...: 199849it [00:18, 22725.78it/s][A
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Reading metadata...: 0it [00:00, ?it/s][A
Reading metadata...: 1it [00:00, 3.44it/s][A
Reading metadata...: 15520it [00:00, 39827.17it/s]
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{'loss': 0.2256, 'learning_rate': 9.946666666666667e-06, 'epoch': 2.01}
{'loss': 0.209, 'learning_rate': 9.891111111111113e-06, 'epoch': 2.01}
05/10/2023 14:21:14 - WARNING - datasets.download.streaming_download_manager - Got disconnected from remote data host. Retrying in 5sec [1/20]
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{'loss': 0.1714, 'learning_rate': 9.780000000000001e-06, 'epoch': 2.02}
{'loss': 0.1657, 'learning_rate': 9.724444444444445e-06, 'epoch': 2.03}
{'loss': 0.1688, 'learning_rate': 9.66888888888889e-06, 'epoch': 2.03}
{'loss': 0.1616, 'learning_rate': 9.613333333333335e-06, 'epoch': 2.04}
{'loss': 0.1541, 'learning_rate': 9.557777777777777e-06, 'epoch': 2.04}
{'loss': 0.1565, 'learning_rate': 9.502222222222223e-06, 'epoch': 2.05}
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20%|██ | 1000/5000 [8:05:54<32:01:14, 28.82s/it][INFO|trainer.py:3138] 2023-05-10 17:47:34,809 >> ***** Running Evaluation *****
[INFO|trainer.py:3142] 2023-05-10 17:47:34,809 >> Num examples: Unknown
[INFO|trainer.py:3143] 2023-05-10 17:47:34,809 >> Batch size = 64
{'loss': 0.1075, 'learning_rate': 8.946666666666669e-06, 'epoch': 4.0}
{'loss': 0.1386, 'learning_rate': 8.891111111111111e-06, 'epoch': 4.01}
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[INFO|trainer_utils.py:693] 2023-05-10 17:47:50,596 >> The following columns in the evaluation set don't have a corresponding argument in `WhisperForConditionalGeneration.forward` and have been ignored: input_length. If input_length are not expected by `WhisperForConditionalGeneration.forward`, you can safely ignore this message.
20%|██ | 1000/5000 [9:02:19<32:01:14, 28.82s/it][INFO|trainer.py:2877] 2023-05-10 18:43:59,730 >> Saving model checkpoint to ./checkpoint-1000
[INFO|configuration_utils.py:458] 2023-05-10 18:43:59,735 >> Configuration saved in ./checkpoint-1000/config.json
[INFO|configuration_utils.py:364] 2023-05-10 18:43:59,739 >> Configuration saved in ./checkpoint-1000/generation_config.json
[INFO|modeling_utils.py:1855] 2023-05-10 18:44:03,168 >> Model weights saved in ./checkpoint-1000/pytorch_model.bin
[INFO|feature_extraction_utils.py:369] 2023-05-10 18:44:03,173 >> Feature extractor saved in ./checkpoint-1000/preprocessor_config.json
[INFO|feature_extraction_utils.py:369] 2023-05-10 18:44:11,165 >> Feature extractor saved in ./preprocessor_config.json
Adding files tracked by Git LFS: ['wandb/run-20230509_115211-hq92t8sj/run-hq92t8sj.wandb', 'wandb/run-20230510_094132-lvsln7ks/run-lvsln7ks.wandb']. This may take a bit of time if the files are large.
{'eval_loss': 0.24644243717193604, 'eval_wer': 9.800036380645496, 'eval_runtime': 3384.9122, 'eval_samples_per_second': 4.585, 'eval_steps_per_second': 0.072, 'epoch': 4.01}
05/10/2023 18:44:21 - WARNING - huggingface_hub.repository - Adding files tracked by Git LFS: ['wandb/run-20230509_115211-hq92t8sj/run-hq92t8sj.wandb', 'wandb/run-20230510_094132-lvsln7ks/run-lvsln7ks.wandb']. This may take a bit of time if the files are large.
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