--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_trainer datasets: - emotion metrics: - accuracy - f1 model-index: - name: distilbert-base-uncased-finetuned-emotion results: - task: name: Text Classification type: text-classification dataset: name: emotion type: emotion config: split split: validation args: split metrics: - name: Accuracy type: accuracy value: 0.9355 - name: F1 type: f1 value: 0.9354396627100748 --- # distilbert-base-uncased-finetuned-emotion This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset. It achieves the following results on the evaluation set: - Loss: 0.1382 - Accuracy: 0.9355 - F1: 0.9354 ## 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: 2e-05 - train_batch_size: 75 - eval_batch_size: 75 - 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 | Accuracy | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | 0.8649 | 1.0 | 214 | 0.3094 | 0.9055 | 0.9049 | | 0.2229 | 2.0 | 428 | 0.1845 | 0.9305 | 0.9311 | | 0.144 | 3.0 | 642 | 0.1556 | 0.941 | 0.9412 | | 0.1111 | 4.0 | 856 | 0.1394 | 0.941 | 0.9409 | | 0.095 | 5.0 | 1070 | 0.1382 | 0.9355 | 0.9354 | ### Framework versions - Transformers 4.34.1 - Pytorch 2.0.1 - Datasets 2.14.6 - Tokenizers 0.14.1