---
base_model: mistralai/Mistral-7B-Instruct-v0.3
library_name: peft
license: apache-2.0
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Mistral-7B_task-2_60-samples_config-2_full_auto
  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. -->

# Mistral-7B_task-2_60-samples_config-2_full_auto

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co./mistralai/Mistral-7B-Instruct-v0.3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8304

## 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 1.1178        | 0.6957  | 2    | 1.1129          |
| 1.1097        | 1.7391  | 5    | 1.0292          |
| 0.9835        | 2.7826  | 8    | 0.9618          |
| 0.927         | 3.8261  | 11   | 0.9095          |
| 0.8549        | 4.8696  | 14   | 0.8467          |
| 0.7961        | 5.9130  | 17   | 0.8090          |
| 0.736         | 6.9565  | 20   | 0.7970          |
| 0.7303        | 8.0     | 23   | 0.7857          |
| 0.712         | 8.6957  | 25   | 0.7822          |
| 0.6783        | 9.7391  | 28   | 0.7827          |
| 0.6731        | 10.7826 | 31   | 0.7834          |
| 0.6412        | 11.8261 | 34   | 0.7850          |
| 0.6011        | 12.8696 | 37   | 0.7915          |
| 0.582         | 13.9130 | 40   | 0.8032          |
| 0.5422        | 14.9565 | 43   | 0.8101          |
| 0.515         | 16.0    | 46   | 0.8304          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1