--- tags: - generated_from_trainer metrics: - accuracy model-index: - name: bert_gec_detect results: [] --- # bert_gec_detect This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5135 - Accuracy: 0.9349 ## 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: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 0.2169 | 1.0 | 1864 | 0.2219 | 0.9330 | | 0.1933 | 2.0 | 3728 | 0.2413 | 0.9321 | | 0.1632 | 3.0 | 5592 | 0.2905 | 0.9295 | | 0.1323 | 4.0 | 7456 | 0.2807 | 0.9346 | | 0.1168 | 5.0 | 9320 | 0.3174 | 0.9334 | | 0.1018 | 6.0 | 11184 | 0.3848 | 0.9346 | | 0.0688 | 7.0 | 13048 | 0.4739 | 0.9325 | | 0.0585 | 8.0 | 14912 | 0.4750 | 0.9347 | | 0.0545 | 9.0 | 16776 | 0.4894 | 0.9337 | | 0.0497 | 10.0 | 18640 | 0.5135 | 0.9349 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu118 - Datasets 2.14.7 - Tokenizers 0.15.0