---
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_lr3.0000000000000004e-05_bs2_ep5_alpha32_rk4_do0.3_wd3.0e-04
  results: []
---

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# pgd_mistral_8bits_lr3.0000000000000004e-05_bs2_ep5_alpha32_rk4_do0.3_wd3.0e-04

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: 0.9577

## 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: 3.0000000000000004e-05
- 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: linear
- lr_scheduler_warmup_steps: 20
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.8635        | 0.9778 | 33   | 2.2032          |
| 1.6403        | 1.9852 | 67   | 1.2905          |
| 1.0775        | 2.9926 | 101  | 1.0257          |
| 0.9356        | 4.0    | 135  | 0.9717          |
| 0.9174        | 4.8889 | 165  | 0.9577          |


### Framework versions

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