|
--- |
|
license: apache-2.0 |
|
base_model: mistralai/Mistral-7B-v0.1 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: mistral-alpaca2k-3e |
|
results: [] |
|
--- |
|
|
|
[<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) |
|
# mistral-alpaca2k-3e |
|
|
|
This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co./mistralai/Mistral-7B-v0.1) on the mhenrichsen/alpaca_2k_test dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.8850 |
|
|
|
## Training procedure |
|
accelerate launch -m axolotl.cli.train examples/mistral/qlora.yml |
|
|
|
### Training hyperparameters |
|
|
|
The following hyperparameters were used during training: |
|
- learning_rate: 0.0002 |
|
- train_batch_size: 2 |
|
- eval_batch_size: 2 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 8 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_steps: 10 |
|
- num_epochs: 3 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 1.392 | 0.0 | 1 | 1.2581 | |
|
| 0.912 | 0.15 | 36 | 0.7686 | |
|
| 0.7114 | 0.3 | 72 | 0.7590 | |
|
| 0.7849 | 0.45 | 108 | 0.7561 | |
|
| 0.693 | 0.61 | 144 | 0.7546 | |
|
| 0.686 | 0.76 | 180 | 0.7538 | |
|
| 0.782 | 0.91 | 216 | 0.7524 | |
|
| 0.5691 | 1.06 | 252 | 0.7700 | |
|
| 0.5295 | 1.21 | 288 | 0.7883 | |
|
| 0.5313 | 1.36 | 324 | 0.7876 | |
|
| 0.4994 | 1.52 | 360 | 0.7971 | |
|
| 0.6007 | 1.67 | 396 | 0.7881 | |
|
| 0.5459 | 1.82 | 432 | 0.7911 | |
|
| 0.5194 | 1.97 | 468 | 0.7924 | |
|
| 0.3376 | 2.12 | 504 | 0.8711 | |
|
| 0.2983 | 2.27 | 540 | 0.8916 | |
|
| 0.341 | 2.43 | 576 | 0.8891 | |
|
| 0.2961 | 2.58 | 612 | 0.8861 | |
|
| 0.2469 | 2.73 | 648 | 0.8860 | |
|
| 0.3535 | 2.88 | 684 | 0.8850 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.2 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.15.0 |
|
- Tokenizers 0.15.0 |
|
|