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

# Mistral-7B-v0.1_district-court-db

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: 0.0357
- Precision Micro: 0.8047
- Precision Macro: 0.6995
- Recall Micro: 0.8047
- Recall Macro: 0.6609
- F1 Micro: 0.8047
- F1 Macro: 0.6661
- Accuracy: 0.8047

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- training_steps: 725

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision Micro | Precision Macro | Recall Micro | Recall Macro | F1 Micro | F1 Macro | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------------:|:---------------:|:------------:|:------------:|:--------:|:--------:|:--------:|
| 0.0886        | 0.08  | 50   | 0.1082          | 0.5774          | 0.3988          | 0.5774       | 0.3124       | 0.5774   | 0.3222   | 0.5774   |
| 0.0572        | 0.16  | 100  | 0.0832          | 0.5877          | 0.4716          | 0.5877       | 0.3681       | 0.5877   | 0.3797   | 0.5877   |
| 0.0496        | 0.24  | 150  | 0.0525          | 0.7311          | 0.5911          | 0.7311       | 0.5747       | 0.7311   | 0.5703   | 0.7311   |
| 0.0541        | 0.32  | 200  | 0.0464          | 0.7566          | 0.6151          | 0.7566       | 0.5606       | 0.7566   | 0.5584   | 0.7566   |
| 0.0481        | 0.4   | 250  | 0.0433          | 0.7811          | 0.6636          | 0.7811       | 0.6514       | 0.7811   | 0.6369   | 0.7811   |
| 0.053         | 0.48  | 300  | 0.0452          | 0.7632          | 0.6936          | 0.7632       | 0.6461       | 0.7632   | 0.6338   | 0.7632   |
| 0.0401        | 0.56  | 350  | 0.0399          | 0.7943          | 0.7381          | 0.7943       | 0.6604       | 0.7943   | 0.6697   | 0.7943   |
| 0.0509        | 0.64  | 400  | 0.0393          | 0.8009          | 0.6546          | 0.8009       | 0.6612       | 0.8009   | 0.6501   | 0.8009   |
| 0.0474        | 0.72  | 450  | 0.0401          | 0.8019          | 0.7255          | 0.8019       | 0.6927       | 0.8019   | 0.6865   | 0.8019   |
| 0.045         | 0.79  | 500  | 0.0379          | 0.8009          | 0.7147          | 0.8009       | 0.7108       | 0.8009   | 0.6977   | 0.8009   |
| 0.0335        | 0.87  | 550  | 0.0369          | 0.8151          | 0.7046          | 0.8151       | 0.7335       | 0.8151   | 0.7135   | 0.8151   |
| 0.0429        | 0.95  | 600  | 0.0367          | 0.7962          | 0.7081          | 0.7962       | 0.6959       | 0.7962   | 0.6878   | 0.7962   |
| 0.0253        | 1.03  | 650  | 0.0342          | 0.8255          | 0.7370          | 0.8255       | 0.6975       | 0.8255   | 0.7098   | 0.8255   |
| 0.0311        | 1.11  | 700  | 0.0357          | 0.8047          | 0.6995          | 0.8047       | 0.6609       | 0.8047   | 0.6661   | 0.8047   |


### Framework versions

- PEFT 0.7.1
- Transformers 4.37.2
- Pytorch 2.1.2+cu121
- Datasets 2.17.1
- Tokenizers 0.15.1