--- license: apache-2.0 tags: - generated_from_trainer metrics: - f1 model-index: - name: distilbert-base-uncased_fold_2_binary results: [] --- # distilbert-base-uncased_fold_2_binary This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.4724 - F1: 0.7604 ## 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: 25 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | |:-------------:|:-----:|:----:|:---------------:|:------:| | No log | 1.0 | 290 | 0.4280 | 0.7515 | | 0.4018 | 2.0 | 580 | 0.4724 | 0.7604 | | 0.4018 | 3.0 | 870 | 0.5336 | 0.7428 | | 0.1995 | 4.0 | 1160 | 0.8367 | 0.7476 | | 0.1995 | 5.0 | 1450 | 0.9242 | 0.7412 | | 0.089 | 6.0 | 1740 | 1.0987 | 0.7410 | | 0.0318 | 7.0 | 2030 | 1.1853 | 0.7584 | | 0.0318 | 8.0 | 2320 | 1.2509 | 0.7500 | | 0.0189 | 9.0 | 2610 | 1.5060 | 0.7258 | | 0.0189 | 10.0 | 2900 | 1.5607 | 0.7534 | | 0.0084 | 11.0 | 3190 | 1.5871 | 0.7476 | | 0.0084 | 12.0 | 3480 | 1.7206 | 0.7338 | | 0.0047 | 13.0 | 3770 | 1.6776 | 0.7340 | | 0.0068 | 14.0 | 4060 | 1.7339 | 0.7546 | | 0.0068 | 15.0 | 4350 | 1.8279 | 0.7504 | | 0.0025 | 16.0 | 4640 | 1.7791 | 0.7411 | | 0.0025 | 17.0 | 4930 | 1.7917 | 0.7444 | | 0.003 | 18.0 | 5220 | 1.7781 | 0.7559 | | 0.0029 | 19.0 | 5510 | 1.8153 | 0.7559 | | 0.0029 | 20.0 | 5800 | 1.7757 | 0.7414 | | 0.0055 | 21.0 | 6090 | 1.8635 | 0.7454 | | 0.0055 | 22.0 | 6380 | 1.8483 | 0.7460 | | 0.001 | 23.0 | 6670 | 1.8620 | 0.7492 | | 0.001 | 24.0 | 6960 | 1.9058 | 0.7508 | | 0.0006 | 25.0 | 7250 | 1.8640 | 0.7504 | ### Framework versions - Transformers 4.21.0 - Pytorch 1.12.0+cu113 - Datasets 2.4.0 - Tokenizers 0.12.1