---
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: 0.8643
- F1 Micro: 0.6606
- F1 Macro: 0.6479
- F1 Weighted: 0.6611

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:-----------:|
| 1.6117        | 0.0154 | 25   | 1.3679          | 0.5541   | 0.4980   | 0.5313      |
| 1.2903        | 0.0308 | 50   | 1.2094          | 0.6156   | 0.5779   | 0.6029      |
| 1.164         | 0.0462 | 75   | 1.0987          | 0.6206   | 0.5931   | 0.6141      |
| 1.1168        | 0.0615 | 100  | 1.1057          | 0.6376   | 0.5883   | 0.6165      |
| 1.026         | 0.0769 | 125  | 0.9896          | 0.6314   | 0.6196   | 0.6328      |
| 0.9481        | 0.0923 | 150  | 0.9619          | 0.6438   | 0.6173   | 0.6373      |
| 0.9797        | 0.1077 | 175  | 0.9549          | 0.6514   | 0.6191   | 0.6411      |
| 1.045         | 0.1231 | 200  | 0.9121          | 0.6541   | 0.6403   | 0.6543      |
| 0.8954        | 0.1385 | 225  | 0.8991          | 0.6595   | 0.6418   | 0.6576      |
| 0.9245        | 0.1538 | 250  | 0.8887          | 0.6588   | 0.6433   | 0.6580      |
| 0.8636        | 0.1692 | 275  | 0.8824          | 0.6602   | 0.6458   | 0.6600      |
| 0.846         | 0.1846 | 300  | 0.8793          | 0.6672   | 0.6451   | 0.6627      |
| 0.8885        | 0.2    | 325  | 0.8820          | 0.6696   | 0.6431   | 0.6624      |
| 0.8323        | 0.2154 | 350  | 0.8652          | 0.6618   | 0.6474   | 0.6616      |
| 0.9313        | 0.2308 | 375  | 0.8654          | 0.6601   | 0.6477   | 0.6608      |
| 0.857         | 0.2462 | 400  | 0.8643          | 0.6606   | 0.6479   | 0.6611      |


### Framework versions

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