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# legal-bert-base-uncased-supreme-court-summaries-batch32

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: 0.6456
- Accuracy: 0.6352

## 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: 7
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.635         | 1.0   | 660  | 0.6169          | 0.63     |
| 0.6           | 2.0   | 1320 | 0.6154          | 0.6337   |
| 0.5619        | 3.0   | 1980 | 0.6456          | 0.6352   |


### Framework versions

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

{"license": "cc-by-sa-4.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "nlpaueb/legal-bert-base-uncased", "model-index": [{"name": "legal-bert-base-uncased-supreme-court-summaries-batch32", "results": []}]}
transformers tensorboard safetensors bert text-classification generated_from_trainer base_model:nlpaueb/legal-bert-base-uncased license:cc-by-sa-4.0 autotrain_compatible endpoints_compatible region:us