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# topic-bert-base-uncased-supreme-court-32batch_5epoch_2e5lr_01wd

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9049
- Accuracy: 0.7414

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3078        | 1.0   | 660  | 0.9307          | 0.7073   |
| 0.811         | 2.0   | 1320 | 0.8368          | 0.7429   |
| 0.6684        | 3.0   | 1980 | 0.8197          | 0.7406   |
| 0.4163        | 4.0   | 2640 | 0.8724          | 0.7443   |
| 0.34          | 5.0   | 3300 | 0.9049          | 0.7414   |


### Framework versions

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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "bert-base-uncased", "model-index": [{"name": "topic-bert-base-uncased-supreme-court-32batch_5epoch_2e5lr_01wd", "results": []}]}
transformers tensorboard safetensors bert text-classification generated_from_trainer base_model:bert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us