---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: mistralai/Mistral-7B-v0.1
model-index:
- name: org_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_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: 0.9527
- F1 Micro: 0.8011
- F1 Macro: 0.7779
- F1 Weighted: 0.8108

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:-----------:|
| 1.5515        | 0.0064 | 25   | 1.3111          | 0.7801   | 0.7504   | 0.7890      |
| 1.2983        | 0.0127 | 50   | 1.2188          | 0.7748   | 0.7572   | 0.7891      |
| 1.2193        | 0.0191 | 75   | 1.1271          | 0.7855   | 0.7583   | 0.7937      |
| 1.1269        | 0.0255 | 100  | 1.0890          | 0.7952   | 0.7639   | 0.8015      |
| 1.0734        | 0.0318 | 125  | 1.0594          | 0.7949   | 0.7635   | 0.8008      |
| 1.0384        | 0.0382 | 150  | 1.0389          | 0.7857   | 0.7614   | 0.7937      |
| 1.0168        | 0.0446 | 175  | 1.0126          | 0.8045   | 0.7794   | 0.8133      |
| 1.0043        | 0.0510 | 200  | 0.9998          | 0.8034   | 0.7786   | 0.8123      |
| 1.0406        | 0.0573 | 225  | 0.9874          | 0.8074   | 0.7803   | 0.8153      |
| 1.0488        | 0.0637 | 250  | 0.9838          | 0.7922   | 0.7664   | 0.8000      |
| 0.9894        | 0.0701 | 275  | 0.9673          | 0.8034   | 0.7780   | 0.8122      |
| 0.9969        | 0.0764 | 300  | 0.9629          | 0.7992   | 0.7720   | 0.8069      |
| 1.0047        | 0.0828 | 325  | 0.9655          | 0.8000   | 0.7689   | 0.8058      |
| 0.9812        | 0.0892 | 350  | 0.9623          | 0.8049   | 0.7839   | 0.8159      |
| 0.9681        | 0.0955 | 375  | 0.9551          | 0.8016   | 0.7794   | 0.8118      |
| 1.0594        | 0.1019 | 400  | 0.9527          | 0.8011   | 0.7779   | 0.8108      |


### Framework versions

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