---
license: mit
tags:
- generated_from_trainer
base_model: law-ai/InLegalBERT
metrics:
- accuracy
model-index:
- name: InLegalBERT-5-epochs-fine-tune
  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-5-epochs-fine-tune

This model is a fine-tuned version of [law-ai/InLegalBERT](https://huggingface.co/law-ai/InLegalBERT) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8945
- Accuracy: 0.8335

## 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-05
- train_batch_size: 8
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0224        | 1.0   | 643  | 0.6162          | 0.8195   |
| 0.55          | 2.0   | 1286 | 0.6389          | 0.8358   |
| 0.4205        | 3.0   | 1929 | 0.7489          | 0.8304   |
| 0.1503        | 4.0   | 2572 | 0.8605          | 0.8335   |
| 0.1065        | 5.0   | 3215 | 0.8945          | 0.8335   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2