--- license: apache-2.0 tags: - generated_from_trainer metrics: - f1 model-index: - name: distilbert-base-uncased_fold_4_binary results: [] --- # distilbert-base-uncased_fold_4_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: 1.2977 - F1: 0.8083 ## 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 | 0.3701 | 0.7903 | | 0.4005 | 2.0 | 578 | 0.3669 | 0.7994 | | 0.4005 | 3.0 | 867 | 0.5038 | 0.7955 | | 0.1945 | 4.0 | 1156 | 0.6353 | 0.8006 | | 0.1945 | 5.0 | 1445 | 0.8974 | 0.7826 | | 0.0909 | 6.0 | 1734 | 0.8533 | 0.7764 | | 0.0389 | 7.0 | 2023 | 0.9969 | 0.7957 | | 0.0389 | 8.0 | 2312 | 1.0356 | 0.7952 | | 0.0231 | 9.0 | 2601 | 1.1538 | 0.7963 | | 0.0231 | 10.0 | 2890 | 1.2011 | 0.7968 | | 0.0051 | 11.0 | 3179 | 1.2329 | 0.7935 | | 0.0051 | 12.0 | 3468 | 1.2829 | 0.8056 | | 0.0066 | 13.0 | 3757 | 1.2946 | 0.7956 | | 0.004 | 14.0 | 4046 | 1.2977 | 0.8083 | | 0.004 | 15.0 | 4335 | 1.3970 | 0.7957 | | 0.0007 | 16.0 | 4624 | 1.3361 | 0.7917 | | 0.0007 | 17.0 | 4913 | 1.5782 | 0.7954 | | 0.0107 | 18.0 | 5202 | 1.4641 | 0.7900 | | 0.0107 | 19.0 | 5491 | 1.4490 | 0.7957 | | 0.0058 | 20.0 | 5780 | 1.4607 | 0.7932 | | 0.0016 | 21.0 | 6069 | 1.5048 | 0.7939 | | 0.0016 | 22.0 | 6358 | 1.5219 | 0.7945 | | 0.0027 | 23.0 | 6647 | 1.4783 | 0.7937 | | 0.0027 | 24.0 | 6936 | 1.4715 | 0.7981 | | 0.0004 | 25.0 | 7225 | 1.4989 | 0.7900 | ### Framework versions - Transformers 4.21.0 - Pytorch 1.12.0+cu113 - Datasets 2.4.0 - Tokenizers 0.12.1