--- license: apache-2.0 tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: distilbert_token_itr0_1e-05_all_01_03_2022-14_33_33 results: [] --- # distilbert_token_itr0_1e-05_all_01_03_2022-14_33_33 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: 0.3255 - Precision: 0.1412 - Recall: 0.25 - F1: 0.1805 - Accuracy: 0.8491 ## 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 | 0.4549 | 0.0228 | 0.0351 | 0.0276 | 0.7734 | | No log | 2.0 | 60 | 0.3577 | 0.0814 | 0.1260 | 0.0989 | 0.8355 | | No log | 3.0 | 90 | 0.3116 | 0.1534 | 0.2648 | 0.1943 | 0.8611 | | No log | 4.0 | 120 | 0.2975 | 0.1792 | 0.2967 | 0.2234 | 0.8690 | | No log | 5.0 | 150 | 0.2935 | 0.1873 | 0.2998 | 0.2305 | 0.8715 | ### Framework versions - Transformers 4.15.0 - Pytorch 1.10.1+cu113 - Datasets 1.18.0 - Tokenizers 0.10.3