File size: 3,499 Bytes
cb4c9bf |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 |
---
license: apache-2.0
base_model: tokyotech-llm/Swallow-MX-8x7b-NVE-v0.1
tags:
- generated_from_trainer
model-index:
- name: outputs/basemodel-swallowmx-8x22b
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
<details><summary>See axolotl config</summary>
axolotl version: `0.4.0`
```yaml
base_model: tokyotech-llm/Swallow-MX-8x7b-NVE-v0.1
model_type: AutoModelForCausalLM
tokenizer_type: LlamaTokenizer
trust_remote_code: true
load_in_8bit: false
load_in_4bit: false
strict: false
chat_template: inst
datasets:
- path: augmxnt/ultra-orca-boros-en-ja-v1
type: sharegpt
dataset_prepared_path: last_run_prepared
val_set_size: 0.05
output_dir: ./outputs/basemodel-swallowmx-8x22b
model_config:
output_router_logits: true
sequence_len: 4096
sample_packing: true
pad_to_sequence_len: true
use_wandb: true
wandb_project: shisa-v2
wandb_entity: augmxnt
wandb_name: shisa-swallowmx-13a47b-v1
global_batch_size: 1
gradient_accumulation_steps: 8
micro_batch_size: 1
num_epochs: 3
# https://github.com/huggingface/transformers/issues/22101
# https://github.com/huggingface/transformers/blob/main/src/transformers/training_args.py#L141
optimizer: paged_adamw_8bit
lr_scheduler: linear
learning_rate: 2e-5
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: true
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
logging_steps: 1
xformers_attention:
flash_attention: true
warmup_ratio: 0.1
evals_per_epoch: 2
eval_table_size:
saves_per_epoch: 1
debug:
deepspeed: axolotl/deepspeed_configs/zero3_bf16.json
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
```
</details><br>
# outputs/basemodel-swallowmx-8x22b
This model is a fine-tuned version of [tokyotech-llm/Swallow-MX-8x7b-NVE-v0.1](https://huggingface.co/tokyotech-llm/Swallow-MX-8x7b-NVE-v0.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4443
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 119
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.5705 | 0.0022 | 1 | 0.5065 |
| 0.505 | 0.4993 | 229 | 0.3910 |
| 0.5258 | 0.9986 | 458 | 0.3654 |
| 0.2964 | 1.4835 | 687 | 0.3786 |
| 0.2923 | 1.9828 | 916 | 0.3669 |
| 0.1462 | 2.4682 | 1145 | 0.4429 |
| 0.1156 | 2.9676 | 1374 | 0.4443 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
|