--- license: apache-2.0 tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: correct_distilBERT_token_itr0_1e-05_all_01_03_2022-15_43_47 results: [] --- # correct_distilBERT_token_itr0_1e-05_all_01_03_2022-15_43_47 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: 0.3343 - Precision: 0.1651 - Recall: 0.3039 - F1: 0.2140 - Accuracy: 0.8493 ## 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 | 30 | 0.4801 | 0.0352 | 0.0591 | 0.0441 | 0.7521 | | No log | 2.0 | 60 | 0.3795 | 0.0355 | 0.0795 | 0.0491 | 0.8020 | | No log | 3.0 | 90 | 0.3359 | 0.0591 | 0.1294 | 0.0812 | 0.8334 | | No log | 4.0 | 120 | 0.3205 | 0.0785 | 0.1534 | 0.1039 | 0.8486 | | No log | 5.0 | 150 | 0.3144 | 0.0853 | 0.1571 | 0.1105 | 0.8516 | ### Framework versions - Transformers 4.15.0 - Pytorch 1.10.1+cu113 - Datasets 1.18.0 - Tokenizers 0.10.3