---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: mistralai/Mistral-7B-v0.1
model-index:
- name: org_modelorg_model
  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. -->

# org_modelorg_model

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: 0.9110
- F1 Micro: 0.8214
- F1 Macro: 0.8156
- F1 Weighted: 0.8234

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 400

### Training results

| Training Loss | Epoch  | Step | Validation Loss | F1 Micro | F1 Macro | F1 Weighted |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:-----------:|
| 1.979         | 0.0154 | 25   | 1.4043          | 0.7220   | 0.7197   | 0.7259      |
| 1.3006        | 0.0308 | 50   | 1.2184          | 0.7775   | 0.7754   | 0.7807      |
| 1.1099        | 0.0462 | 75   | 1.1320          | 0.8010   | 0.7970   | 0.8040      |
| 1.1383        | 0.0615 | 100  | 1.0762          | 0.8039   | 0.8007   | 0.8072      |
| 1.0121        | 0.0769 | 125  | 1.0230          | 0.8010   | 0.7967   | 0.8037      |
| 1.0296        | 0.0923 | 150  | 0.9966          | 0.8099   | 0.8056   | 0.8130      |
| 1.0485        | 0.1077 | 175  | 0.9745          | 0.8111   | 0.8063   | 0.8139      |
| 0.9996        | 0.1231 | 200  | 0.9647          | 0.8030   | 0.7984   | 0.8052      |
| 0.9815        | 0.1385 | 225  | 0.9490          | 0.8160   | 0.8099   | 0.8178      |
| 0.9456        | 0.1538 | 250  | 0.9378          | 0.8073   | 0.8033   | 0.8099      |
| 0.8896        | 0.1692 | 275  | 0.9298          | 0.8143   | 0.8091   | 0.8164      |
| 0.994         | 0.1846 | 300  | 0.9239          | 0.8064   | 0.8030   | 0.8094      |
| 0.8588        | 0.2    | 325  | 0.9142          | 0.8119   | 0.8079   | 0.8145      |
| 0.8971        | 0.2154 | 350  | 0.9139          | 0.8216   | 0.8158   | 0.8236      |
| 0.9647        | 0.2308 | 375  | 0.9133          | 0.8223   | 0.8163   | 0.8242      |
| 0.9352        | 0.2462 | 400  | 0.9110          | 0.8214   | 0.8156   | 0.8234      |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.3.0+cu118
- Datasets 2.19.0
- Tokenizers 0.19.1