|
--- |
|
license: other |
|
library_name: peft |
|
tags: |
|
- trl |
|
- sft |
|
- generated_from_trainer |
|
base_model: 01-ai/Yi-6B |
|
model-index: |
|
- name: Yi-6B-ruozhiba-1e-5-50 |
|
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. --> |
|
|
|
# Yi-6B-ruozhiba-1e-5-50 |
|
|
|
This model is a fine-tuned version of [01-ai/Yi-6B](https://huggingface.co/01-ai/Yi-6B) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.9875 |
|
|
|
## 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: 1e-05 |
|
- train_batch_size: 4 |
|
- eval_batch_size: 4 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 20 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 1.8114 | 4.0 | 220 | 1.8505 | |
|
| 1.6723 | 5.0 | 275 | 1.8372 | |
|
| 1.6532 | 6.0 | 330 | 1.8296 | |
|
| 1.7187 | 7.0 | 385 | 1.8273 | |
|
| 1.6945 | 8.0 | 440 | 1.8345 | |
|
| 1.5494 | 9.0 | 495 | 1.8452 | |
|
| 1.5329 | 10.0 | 550 | 1.8665 | |
|
| 1.4105 | 11.0 | 605 | 1.8877 | |
|
| 1.3862 | 12.0 | 660 | 1.9066 | |
|
| 1.4126 | 13.0 | 715 | 1.9303 | |
|
| 1.388 | 14.0 | 770 | 1.9449 | |
|
| 1.3653 | 15.0 | 825 | 1.9637 | |
|
| 1.361 | 16.0 | 880 | 1.9738 | |
|
| 1.2944 | 17.0 | 935 | 1.9819 | |
|
| 1.3433 | 18.0 | 990 | 1.9856 | |
|
| 1.2058 | 19.0 | 1045 | 1.9871 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.7.1 |
|
- Transformers 4.36.2 |
|
- Pytorch 2.2.2+cu118 |
|
- Datasets 2.14.6 |
|
- Tokenizers 0.15.2 |
