--- license: apache-2.0 tags: - generated_from_trainer metrics: - f1 model-index: - name: distilbert-base-uncased_fold_7_ternary_v1 results: [] --- # distilbert-base-uncased_fold_7_ternary_v1 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: 2.0462 - F1: 0.7836 ## 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 | 291 | 0.5719 | 0.7490 | | 0.5541 | 2.0 | 582 | 0.5563 | 0.7836 | | 0.5541 | 3.0 | 873 | 0.7301 | 0.7849 | | 0.2509 | 4.0 | 1164 | 0.8073 | 0.7926 | | 0.2509 | 5.0 | 1455 | 1.0842 | 0.7823 | | 0.1182 | 6.0 | 1746 | 1.1721 | 0.7900 | | 0.0537 | 7.0 | 2037 | 1.4060 | 0.7785 | | 0.0537 | 8.0 | 2328 | 1.4497 | 0.7836 | | 0.0262 | 9.0 | 2619 | 1.4722 | 0.7708 | | 0.0262 | 10.0 | 2910 | 1.6529 | 0.7772 | | 0.0131 | 11.0 | 3201 | 1.6573 | 0.7862 | | 0.0131 | 12.0 | 3492 | 1.6986 | 0.7823 | | 0.0115 | 13.0 | 3783 | 1.7765 | 0.7810 | | 0.0098 | 14.0 | 4074 | 1.8036 | 0.7862 | | 0.0098 | 15.0 | 4365 | 1.7684 | 0.7926 | | 0.0028 | 16.0 | 4656 | 1.8385 | 0.7836 | | 0.0028 | 17.0 | 4947 | 1.7903 | 0.7887 | | 0.0054 | 18.0 | 5238 | 1.9065 | 0.7810 | | 0.0007 | 19.0 | 5529 | 1.9331 | 0.7875 | | 0.0007 | 20.0 | 5820 | 1.9384 | 0.7849 | | 0.0006 | 21.0 | 6111 | 1.8687 | 0.7887 | | 0.0006 | 22.0 | 6402 | 2.0603 | 0.7785 | | 0.0009 | 23.0 | 6693 | 2.0403 | 0.7836 | | 0.0009 | 24.0 | 6984 | 2.0348 | 0.7810 | | 0.0005 | 25.0 | 7275 | 2.0462 | 0.7836 | ### Framework versions - Transformers 4.21.0 - Pytorch 1.12.0+cu113 - Datasets 2.4.0 - Tokenizers 0.12.1