--- license: apache-2.0 base_model: lilyray/albert_emotion tags: - generated_from_trainer datasets: - emotion metrics: - accuracy model-index: - name: albert_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: 0.9295 --- # albert_emotion This model is a fine-tuned version of [lilyray/albert_emotion](https://huggingface.co/lilyray/albert_emotion) on the emotion dataset. It achieves the following results on the evaluation set: - Loss: 0.2391 - Accuracy: 0.9295 ## 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: 9.363600088100325e-06 - train_batch_size: 4 - eval_batch_size: 8 - seed: 19 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 1 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.1744 | 1.0 | 4000 | 0.2001 | 0.938 | ### Framework versions - Transformers 4.38.2 - Pytorch 2.1.0+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2