---
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: Mistral_final_Task2_2.0
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Mistral_final_Task2_2.0

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: 0.5570
- Accuracy: 0.8943
- Precision: 0.9184
- Recall: 0.8661
- F1 score: 0.8915

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1 score |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
| 0.9274        | 0.5450 | 200  | 0.6669          | 0.8371   | 0.9072    | 0.7521 | 0.8224   |
| 0.5321        | 1.0899 | 400  | 1.0293          | 0.7986   | 0.9861    | 0.6068 | 0.7513   |
| 0.4279        | 1.6349 | 600  | 1.0278          | 0.7586   | 0.6904    | 0.9402 | 0.7961   |
| 0.3054        | 2.1798 | 800  | 0.4428          | 0.8714   | 0.8575    | 0.8917 | 0.8743   |
| 0.2297        | 2.7248 | 1000 | 0.5243          | 0.8743   | 0.9428    | 0.7977 | 0.8642   |
| 0.1798        | 3.2698 | 1200 | 0.4710          | 0.8971   | 0.9043    | 0.8889 | 0.8966   |
| 0.158         | 3.8147 | 1400 | 0.5673          | 0.8986   | 0.9545    | 0.8376 | 0.8923   |
| 0.0921        | 4.3597 | 1600 | 0.5847          | 0.8743   | 0.8380    | 0.9288 | 0.8811   |
| 0.063         | 4.9046 | 1800 | 0.5570          | 0.8943   | 0.9184    | 0.8661 | 0.8915   |


### Framework versions

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