--- tags: - generated_from_trainer datasets: - marsyas/gtzan metrics: - accuracy model-index: - name: Hubert_emotion-finetuned-gtzan-efficient results: [] --- # Hubert_emotion-finetuned-gtzan-efficient This model is a fine-tuned version of [Rajaram1996/Hubert_emotion](https://huggingface.co/Rajaram1996/Hubert_emotion) on the GTZAN dataset. It achieves the following results on the evaluation set: - Loss: 1.2341 - Accuracy: 0.65 ## 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 - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 2.2127 | 1.0 | 113 | 2.2191 | 0.25 | | 1.9102 | 2.0 | 226 | 2.0018 | 0.37 | | 1.7139 | 3.0 | 339 | 1.7588 | 0.4 | | 1.5825 | 4.0 | 452 | 1.5608 | 0.41 | | 1.1426 | 5.0 | 565 | 1.4300 | 0.5 | | 1.8976 | 6.0 | 678 | 1.1726 | 0.56 | | 0.9303 | 7.0 | 791 | 1.1559 | 0.56 | | 0.8845 | 8.0 | 904 | 1.1501 | 0.65 | | 0.2069 | 9.0 | 1017 | 1.2055 | 0.58 | | 1.9863 | 10.0 | 1130 | 1.0804 | 0.62 | | 2.0317 | 11.0 | 1243 | 1.2341 | 0.65 | ### Framework versions - Transformers 4.30.2 - Pytorch 2.1.0.dev20230627+cu121 - Datasets 2.13.1 - Tokenizers 0.13.3