---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: mistralai/Mistral-7B-v0.1
metrics:
- accuracy
- precision
- recall
model-index:
- name: mistralai_compi_data
  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. -->

# mistralai_compi_data

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co./mistralai/Mistral-7B-v0.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4322
- Accuracy: 0.8761
- Precision: 0.8564
- Recall: 0.8995
- F1 score: 0.8774

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1 score |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
| 1.3663        | 0.2604 | 200  | 1.1150          | 0.7692   | 0.8851    | 0.6111 | 0.7230   |
| 0.8905        | 0.5208 | 400  | 0.6190          | 0.8318   | 0.8487    | 0.8016 | 0.8245   |
| 0.7007        | 0.7812 | 600  | 0.5719          | 0.8462   | 0.9140    | 0.7593 | 0.8295   |
| 0.5215        | 1.0417 | 800  | 0.4315          | 0.8696   | 0.8819    | 0.8492 | 0.8652   |
| 0.2955        | 1.3021 | 1000 | 0.6376          | 0.8592   | 0.8140    | 0.9259 | 0.8663   |
| 0.3254        | 1.5625 | 1200 | 0.5735          | 0.8735   | 0.9607    | 0.7751 | 0.8580   |
| 0.3075        | 1.8229 | 1400 | 0.4322          | 0.8761   | 0.8564    | 0.8995 | 0.8774   |


### Framework versions

- PEFT 0.11.1
- Transformers 4.44.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1