---
license: cc-by-sa-4.0
base_model: nlpaueb/legal-bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: legal-bert-base-uncased-supreme-court-summaries-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. -->

# legal-bert-base-uncased-supreme-court-summaries-2

This model is a fine-tuned version of [nlpaueb/legal-bert-base-uncased](https://huggingface.co/nlpaueb/legal-bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5445
- Accuracy: 0.6156

## 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: 16
- eval_batch_size: 16
- seed: 47
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6228        | 1.0   | 1320 | 0.6084          | 0.6267   |
| 0.5672        | 2.0   | 2640 | 0.6318          | 0.6315   |
| 0.4577        | 3.0   | 3960 | 0.7553          | 0.6248   |
| 0.3173        | 4.0   | 5280 | 0.9317          | 0.6207   |
| 0.2069        | 5.0   | 6600 | 1.2745          | 0.6163   |
| 0.146         | 6.0   | 7920 | 1.5445          | 0.6156   |


### Framework versions

- Transformers 4.35.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1