---
license: mit
base_model: law-ai/InLegalBERT
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: InLegalBERT-lora-text-classification
  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. -->

# InLegalBERT-lora-text-classification

This model is a fine-tuned version of [law-ai/InLegalBERT](https://huggingface.co/law-ai/InLegalBERT) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0550
- Accuracy: {'accuracy': 0.6449893390191898}

## 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: 2e-05
- 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
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy                         |
|:-------------:|:-----:|:----:|:---------------:|:--------------------------------:|
| No log        | 1.0   | 235  | 1.1448          | {'accuracy': 0.6151385927505331} |
| No log        | 2.0   | 470  | 1.0553          | {'accuracy': 0.6380597014925373} |
| 1.2222        | 3.0   | 705  | 1.0427          | {'accuracy': 0.6316631130063965} |
| 1.2222        | 4.0   | 940  | 1.0490          | {'accuracy': 0.6428571428571429} |
| 0.8111        | 5.0   | 1175 | 1.0550          | {'accuracy': 0.6449893390191898} |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1