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Hubert_emotion-finetuned-gtzan-efficient
This model is a fine-tuned version of 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
