---
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_lr0.004_alpha32_rk4_do0.2_wd3.0e-03
  results: []
---

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# pgd_mistral_8bits_lr0.004_alpha32_rk4_do0.2_wd3.0e-03

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: 4.7590

## 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: 0.004
- 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: 50
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.1711        | 1.0   | 15   | 1.1259          |
| 2.5313        | 2.0   | 30   | 9.7541          |
| 8.0828        | 3.0   | 45   | 6.5207          |
| 5.9822        | 4.0   | 60   | 5.0761          |
| 4.8191        | 5.0   | 75   | 4.7590          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1