--- base_model: google/reformer-crime-and-punishment tags: - generated_from_trainer metrics: - accuracy model-index: - name: reformer_model results: [] --- # reformer_model This model is a fine-tuned version of [google/reformer-crime-and-punishment](https://huggingface.co/google/reformer-crime-and-punishment) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6693 - Accuracy: 0.561 ## 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: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.6841 | 1.0 | 625 | 0.6725 | 0.559 | | 0.6789 | 2.0 | 1250 | 0.6693 | 0.561 | ### Framework versions - Transformers 4.40.2 - Pytorch 2.3.0+cpu - Datasets 2.19.1 - Tokenizers 0.19.1