--- license: cc-by-sa-4.0 base_model: nlpaueb/legal-bert-base-uncased tags: - generated_from_trainer metrics: - accuracy model-index: - name: topic-legal-bert-base-uncased-supreme-court-32batch_5epoch_2e5lr_01wd results: [] --- # topic-legal-bert-base-uncased-supreme-court-32batch_5epoch_2e5lr_01wd 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: 0.8083 - Accuracy: 0.7799 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 1.146 | 1.0 | 660 | 0.7959 | 0.7525 | | 0.6965 | 2.0 | 1320 | 0.7491 | 0.7688 | | 0.5724 | 3.0 | 1980 | 0.7384 | 0.7807 | | 0.3395 | 4.0 | 2640 | 0.7731 | 0.7847 | | 0.2824 | 5.0 | 3300 | 0.8083 | 0.7799 | ### Framework versions - Transformers 4.35.1 - Pytorch 2.1.0+cu121 - Datasets 2.14.6 - Tokenizers 0.14.1