---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: mistralai/Mistral-7B-v0.1
metrics:
- accuracy
model-index:
- name: lex_glue_ledgar_2
  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. -->

# lex_glue_ledgar_2

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5472
- Accuracy: 0.846
- F1 Macro: 0.7622
- F1 Micro: 0.846

## 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: 5e-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 0.8576        | 0.27  | 250  | 0.9224          | 0.7704   | 0.6393   | 0.7704   |
| 0.7735        | 0.53  | 500  | 0.7367          | 0.806    | 0.6941   | 0.806    |
| 0.7498        | 0.8   | 750  | 0.6500          | 0.8211   | 0.7187   | 0.8211   |
| 0.4705        | 1.07  | 1000 | 0.6080          | 0.8341   | 0.7484   | 0.8341   |
| 0.4717        | 1.33  | 1250 | 0.6027          | 0.8364   | 0.7470   | 0.8364   |
| 0.4793        | 1.6   | 1500 | 0.5638          | 0.8418   | 0.7537   | 0.8418   |
| 0.4884        | 1.87  | 1750 | 0.5472          | 0.846    | 0.7622   | 0.846    |
| 0.2172        | 2.13  | 2000 | 0.5798          | 0.8515   | 0.7693   | 0.8515   |
| 0.224         | 2.4   | 2250 | 0.6039          | 0.8525   | 0.7700   | 0.8525   |
| 0.1555        | 2.67  | 2500 | 0.5900          | 0.8557   | 0.7764   | 0.8557   |
| 0.1949        | 2.93  | 2750 | 0.5838          | 0.8578   | 0.7807   | 0.8578   |


### Framework versions

- PEFT 0.9.0
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2