|
--- |
|
license: llama2 |
|
base_model: lmsys/vicuna-7b-v1.5 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: finetune_cs_20 |
|
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. --> |
|
|
|
# finetune_cs_20 |
|
|
|
This model is a fine-tuned version of [lmsys/vicuna-7b-v1.5](https://huggingface.co/lmsys/vicuna-7b-v1.5) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.9803 |
|
|
|
## 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: 0.0001 |
|
- train_batch_size: 4 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 5 |
|
- num_epochs: 20 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 1.7173 | 1.0 | 150 | 1.6256 | |
|
| 1.5959 | 2.0 | 300 | 1.6775 | |
|
| 0.5699 | 3.0 | 450 | 1.9236 | |
|
| 0.4921 | 4.0 | 600 | 2.1318 | |
|
| 0.3044 | 5.0 | 750 | 2.2606 | |
|
| 0.2809 | 6.0 | 900 | 2.3494 | |
|
| 0.2299 | 7.0 | 1050 | 2.4316 | |
|
| 0.2073 | 8.0 | 1200 | 2.4576 | |
|
| 0.1851 | 9.0 | 1350 | 2.4981 | |
|
| 0.1906 | 10.0 | 1500 | 2.6060 | |
|
| 0.1616 | 11.0 | 1650 | 2.6427 | |
|
| 0.1529 | 12.0 | 1800 | 2.6856 | |
|
| 0.1453 | 13.0 | 1950 | 2.7683 | |
|
| 0.1507 | 14.0 | 2100 | 2.7889 | |
|
| 0.1607 | 15.0 | 2250 | 2.8477 | |
|
| 0.1545 | 16.0 | 2400 | 2.8710 | |
|
| 0.1598 | 17.0 | 2550 | 2.8968 | |
|
| 0.1593 | 18.0 | 2700 | 2.9389 | |
|
| 0.1479 | 19.0 | 2850 | 2.9629 | |
|
| 0.1298 | 20.0 | 3000 | 2.9803 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.2 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.15.0 |
|
- Tokenizers 0.15.0 |
|
|