--- license: apache-2.0 tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: DistilBERT_FINAL_ctxSentence_TRAIN_editorials_TEST_NULL_second_train_set_null_False results: [] --- # DistilBERT_FINAL_ctxSentence_TRAIN_editorials_TEST_NULL_second_train_set_null_False 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: 4.8119 - Precision: 0.2752 - Recall: 0.9522 - F1: 0.4270 - Accuracy: 0.2849 ## 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: 1e-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 | 166 | 0.0726 | 0.9827 | 1.0 | 0.9913 | 0.9828 | | No log | 2.0 | 332 | 0.0569 | 0.9827 | 1.0 | 0.9913 | 0.9828 | | No log | 3.0 | 498 | 0.0434 | 0.9884 | 1.0 | 0.9942 | 0.9885 | | 0.1021 | 4.0 | 664 | 0.0505 | 0.9884 | 1.0 | 0.9942 | 0.9885 | | 0.1021 | 5.0 | 830 | 0.0472 | 0.9884 | 1.0 | 0.9942 | 0.9885 | ### Framework versions - Transformers 4.15.0 - Pytorch 1.10.1+cu113 - Datasets 1.18.0 - Tokenizers 0.10.3