|
--- |
|
library_name: peft |
|
license: apache-2.0 |
|
base_model: TheBloke/Mistral-7B-Instruct-v0.2-GPTQ |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: shawgpt-ft |
|
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. --> |
|
|
|
# shawgpt-ft |
|
|
|
This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.2-GPTQ](https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.2-GPTQ) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.7413 |
|
|
|
## 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: 0.0002 |
|
- train_batch_size: 4 |
|
- eval_batch_size: 4 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 16 |
|
- optimizer: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 2 |
|
- num_epochs: 10 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:------:|:----:|:---------------:| |
|
| 4.5918 | 0.9231 | 3 | 3.9644 | |
|
| 4.0441 | 1.8462 | 6 | 3.4429 | |
|
| 3.4677 | 2.7692 | 9 | 2.9817 | |
|
| 2.2518 | 4.0 | 13 | 2.5502 | |
|
| 2.6491 | 4.9231 | 16 | 2.2852 | |
|
| 2.3093 | 5.8462 | 19 | 2.0790 | |
|
| 2.0483 | 6.7692 | 22 | 1.9019 | |
|
| 1.429 | 8.0 | 26 | 1.7849 | |
|
| 1.8173 | 8.9231 | 29 | 1.7459 | |
|
| 1.2673 | 9.2308 | 30 | 1.7413 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.14.0 |
|
- Transformers 4.46.3 |
|
- Pytorch 2.5.1+cu121 |
|
- Datasets 3.2.0 |
|
- Tokenizers 0.20.3 |