|
--- |
|
license: apache-2.0 |
|
base_model: mistralai/Mistral-7B-v0.1 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: zephyr-7b-sft-lora-accum4-lr5e_5 |
|
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. --> |
|
|
|
# zephyr-7b-sft-lora-accum4-lr5e_5 |
|
|
|
This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.5833 |
|
|
|
## 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: 5e-05 |
|
- train_batch_size: 4 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- num_devices: 2 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 32 |
|
- total_eval_batch_size: 16 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine |
|
- num_epochs: 50.0 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 1.8243 | 0.55 | 13 | 1.6684 | |
|
| 1.5291 | 1.57 | 27 | 1.4003 | |
|
| 1.2355 | 2.55 | 40 | 1.1808 | |
|
| 1.1393 | 3.57 | 54 | 1.0949 | |
|
| 1.0659 | 4.55 | 67 | 1.0457 | |
|
| 1.0196 | 5.57 | 81 | 1.0065 | |
|
| 0.9831 | 6.55 | 94 | 0.9686 | |
|
| 0.9281 | 7.57 | 108 | 0.9255 | |
|
| 0.8678 | 8.55 | 121 | 0.8814 | |
|
| 0.8054 | 9.57 | 135 | 0.8275 | |
|
| 0.7683 | 10.55 | 148 | 0.7861 | |
|
| 0.6906 | 11.57 | 162 | 0.7272 | |
|
| 0.6246 | 12.55 | 175 | 0.6795 | |
|
| 0.5813 | 13.57 | 189 | 0.6364 | |
|
| 0.5253 | 14.55 | 202 | 0.6078 | |
|
| 0.5149 | 15.57 | 216 | 0.5811 | |
|
| 0.4949 | 16.55 | 229 | 0.5605 | |
|
| 0.4644 | 17.57 | 243 | 0.5462 | |
|
| 0.458 | 18.55 | 256 | 0.5346 | |
|
| 0.4294 | 19.57 | 270 | 0.5202 | |
|
| 0.4143 | 20.55 | 283 | 0.5177 | |
|
| 0.4161 | 21.57 | 297 | 0.5108 | |
|
| 0.4128 | 22.55 | 310 | 0.5057 | |
|
| 0.4055 | 23.57 | 324 | 0.5071 | |
|
| 0.3937 | 24.55 | 337 | 0.5058 | |
|
| 0.3967 | 25.57 | 351 | 0.5017 | |
|
| 0.3754 | 26.55 | 364 | 0.4998 | |
|
| 0.3742 | 27.57 | 378 | 0.5019 | |
|
| 0.3756 | 28.55 | 391 | 0.5019 | |
|
| 0.3652 | 29.57 | 405 | 0.5061 | |
|
| 0.3597 | 30.55 | 418 | 0.5076 | |
|
| 0.3609 | 31.57 | 432 | 0.5079 | |
|
| 0.3581 | 32.55 | 445 | 0.5108 | |
|
| 0.3426 | 33.57 | 459 | 0.5117 | |
|
| 0.3481 | 34.55 | 472 | 0.5141 | |
|
| 0.3435 | 35.57 | 486 | 0.5150 | |
|
| 0.3317 | 36.55 | 499 | 0.5245 | |
|
| 0.3387 | 37.57 | 513 | 0.5239 | |
|
| 0.332 | 38.55 | 526 | 0.5319 | |
|
| 0.3334 | 39.57 | 540 | 0.5342 | |
|
| 0.323 | 40.55 | 553 | 0.5388 | |
|
| 0.3144 | 41.57 | 567 | 0.5423 | |
|
| 0.3092 | 42.55 | 580 | 0.5465 | |
|
| 0.3084 | 43.57 | 594 | 0.5481 | |
|
| 0.3091 | 44.55 | 607 | 0.5605 | |
|
| 0.3044 | 45.57 | 621 | 0.5606 | |
|
| 0.303 | 46.55 | 634 | 0.5683 | |
|
| 0.2896 | 47.57 | 648 | 0.5722 | |
|
| 0.2854 | 48.55 | 661 | 0.5778 | |
|
| 0.291 | 49.57 | 675 | 0.5826 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.0 |
|
- Pytorch 2.1.0 |
|
- Datasets 2.14.6 |
|
- Tokenizers 0.14.1 |
|
|
