--- license: apache-2.0 tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: distilBERT_token_itr0_1e-05_all_01_03_2022-15_14_04 results: [] --- # distilBERT_token_itr0_1e-05_all_01_03_2022-15_14_04 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: 0.3121 - Precision: 0.1204 - Recall: 0.2430 - F1: 0.1611 - Accuracy: 0.8538 ## 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 | 0.4480 | 0.0209 | 0.0223 | 0.0216 | 0.7794 | | No log | 2.0 | 60 | 0.3521 | 0.0559 | 0.1218 | 0.0767 | 0.8267 | | No log | 3.0 | 90 | 0.3177 | 0.1208 | 0.2504 | 0.1629 | 0.8487 | | No log | 4.0 | 120 | 0.3009 | 0.1296 | 0.2607 | 0.1731 | 0.8602 | | No log | 5.0 | 150 | 0.2988 | 0.1393 | 0.2693 | 0.1836 | 0.8599 | ### Framework versions - Transformers 4.15.0 - Pytorch 1.10.1+cu113 - Datasets 1.18.0 - Tokenizers 0.10.3