--- license: apache-2.0 tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: finetuned_token_2e-05_16_02_2022-14_37_42 results: [] --- # finetuned_token_2e-05_16_02_2022-14_37_42 This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.1722 - Precision: 0.3378 - Recall: 0.3615 - F1: 0.3492 - Accuracy: 0.9448 ## 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: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | No log | 1.0 | 38 | 0.3781 | 0.1512 | 0.2671 | 0.1931 | 0.8216 | | No log | 2.0 | 76 | 0.3020 | 0.1748 | 0.2938 | 0.2192 | 0.8551 | | No log | 3.0 | 114 | 0.2723 | 0.1938 | 0.3339 | 0.2452 | 0.8663 | | No log | 4.0 | 152 | 0.2574 | 0.2119 | 0.3506 | 0.2642 | 0.8727 | | No log | 5.0 | 190 | 0.2521 | 0.2121 | 0.3623 | 0.2676 | 0.8756 | ### Framework versions - Transformers 4.15.0 - Pytorch 1.10.1+cu113 - Datasets 1.18.0 - Tokenizers 0.10.3