--- license: apache-2.0 tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: finetuned_token_itr0_3e-05_essays_16_02_2022-21_02_59 results: [] --- # finetuned_token_itr0_3e-05_essays_16_02_2022-21_02_59 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: 0.2374 - Precision: 0.4766 - Recall: 0.5549 - F1: 0.5127 - Accuracy: 0.9173 ## 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: 3e-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 | 11 | 0.4155 | 0.1569 | 0.3168 | 0.2099 | 0.8163 | | No log | 2.0 | 22 | 0.3584 | 0.3827 | 0.5725 | 0.4587 | 0.8691 | | No log | 3.0 | 33 | 0.3483 | 0.4353 | 0.5649 | 0.4917 | 0.8737 | | No log | 4.0 | 44 | 0.3187 | 0.4403 | 0.5916 | 0.5049 | 0.8770 | | No log | 5.0 | 55 | 0.3188 | 0.4463 | 0.6031 | 0.5130 | 0.8806 | ### Framework versions - Transformers 4.15.0 - Pytorch 1.10.1+cu113 - Datasets 1.18.0 - Tokenizers 0.10.3