---
base_model: mistralai/Mistral-7B-Instruct-v0.3
library_name: peft
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: pgd_mistral_8bits_lr0.0002_alpha32_rk4_do0.1_wd1.0e-02
  results: []
---

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# pgd_mistral_8bits_lr0.0002_alpha32_rk4_do0.1_wd1.0e-02

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7793

## 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: 3
- eval_batch_size: 3
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 12
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 3.0296        | 0.9778 | 11   | 2.3415          |
| 1.8108        | 1.9556 | 22   | 1.1645          |
| 1.0071        | 2.9333 | 33   | 0.8704          |
| 0.7805        | 4.0    | 45   | 0.8074          |
| 0.7974        | 4.9778 | 56   | 0.7788          |
| 0.7645        | 5.9556 | 67   | 0.7678          |
| 0.7508        | 6.9333 | 78   | 0.7640          |
| 0.675         | 8.0    | 90   | 0.7635          |
| 0.7262        | 8.9778 | 101  | 0.7708          |
| 0.6817        | 9.7778 | 110  | 0.7793          |


### Framework versions

- PEFT 0.10.1.dev0
- Transformers 4.43.4
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1