--- tags: - generated_from_trainer datasets: - emotion metrics: - accuracy model-index: - name: bnb-sentiment-model-saagie results: - task: name: Text Classification type: text-classification dataset: name: emotion type: emotion args: split metrics: - name: Accuracy type: accuracy value: 0.9444444444444444 --- # bnb-sentiment-model-saagie This model is a fine-tuned version of [j-hartmann/emotion-english-distilroberta-base](https://huggingface.co/j-hartmann/emotion-english-distilroberta-base) on the emotion dataset. It achieves the following results on the evaluation set: - Loss: 0.3581 - Accuracy: 0.9444 ## 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: 5e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 8 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 0.3724 | 1.0 | 1875 | 0.1799 | 0.9367 | | 0.2118 | 2.0 | 3750 | 0.1918 | 0.9456 | | 0.1792 | 3.0 | 5625 | 0.1791 | 0.95 | | 0.1489 | 4.0 | 7500 | 0.1479 | 0.9489 | | 0.1168 | 5.0 | 9375 | 0.2561 | 0.9444 | | 0.081 | 6.0 | 11250 | 0.2863 | 0.9411 | | 0.0521 | 7.0 | 13125 | 0.3168 | 0.9467 | | 0.0345 | 8.0 | 15000 | 0.3581 | 0.9444 | ### Framework versions - Transformers 4.18.0 - Pytorch 1.8.1 - Datasets 2.12.0 - Tokenizers 0.12.1