--- license: apache-2.0 tags: - generated_from_trainer metrics: - f1 model-index: - name: distilbert-base-uncased_fold_4_ternary results: [] --- # distilbert-base-uncased_fold_4_ternary 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: 1.2981 - F1: 0.7565 ## 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 | 289 | 0.5588 | 0.6984 | | 0.5547 | 2.0 | 578 | 0.5283 | 0.7336 | | 0.5547 | 3.0 | 867 | 0.7038 | 0.7202 | | 0.2479 | 4.0 | 1156 | 0.8949 | 0.7284 | | 0.2479 | 5.0 | 1445 | 0.9959 | 0.7286 | | 0.1181 | 6.0 | 1734 | 1.0663 | 0.7311 | | 0.0508 | 7.0 | 2023 | 1.2377 | 0.7054 | | 0.0508 | 8.0 | 2312 | 1.2981 | 0.7565 | | 0.0185 | 9.0 | 2601 | 1.3532 | 0.7407 | | 0.0185 | 10.0 | 2890 | 1.5365 | 0.7333 | | 0.0103 | 11.0 | 3179 | 1.5184 | 0.7423 | | 0.0103 | 12.0 | 3468 | 1.6009 | 0.7420 | | 0.0123 | 13.0 | 3757 | 1.6395 | 0.7402 | | 0.008 | 14.0 | 4046 | 1.6838 | 0.7429 | | 0.008 | 15.0 | 4335 | 1.6176 | 0.7490 | | 0.0012 | 16.0 | 4624 | 1.7873 | 0.7345 | | 0.0012 | 17.0 | 4913 | 1.6761 | 0.7412 | | 0.0044 | 18.0 | 5202 | 1.7356 | 0.7417 | | 0.0044 | 19.0 | 5491 | 1.7686 | 0.7502 | | 0.0045 | 20.0 | 5780 | 1.7668 | 0.7406 | | 0.0017 | 21.0 | 6069 | 1.8411 | 0.7381 | | 0.0017 | 22.0 | 6358 | 1.8147 | 0.7469 | | 0.0012 | 23.0 | 6647 | 1.8028 | 0.7489 | | 0.0012 | 24.0 | 6936 | 1.8147 | 0.7453 | | 0.0026 | 25.0 | 7225 | 1.8257 | 0.7475 | ### Framework versions - Transformers 4.21.0 - Pytorch 1.12.0+cu113 - Datasets 2.4.0 - Tokenizers 0.12.1