song-coherency-classifier
This model is a fine-tuned version of distilbert/distilroberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1299
- F1: [0.9763779527559054, 0.9757412398921832]
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| No log | 1.0 | 190 | 0.2172 | [0.9460154241645244, 0.9421487603305784] |
| No log | 2.0 | 380 | 0.2073 | [0.9487179487179487, 0.9447513812154695] |
| 0.2175 | 3.0 | 570 | 0.2125 | [0.9487179487179487, 0.9447513812154695] |
| 0.2175 | 4.0 | 760 | 0.1431 | [0.9649595687331537, 0.9658792650918635] |
| 0.2175 | 5.0 | 950 | 0.1467 | [0.9711286089238844, 0.9703504043126685] |
| 0.131 | 6.0 | 1140 | 0.1400 | [0.9711286089238844, 0.9703504043126685] |
| 0.131 | 7.0 | 1330 | 0.1238 | [0.9736842105263158, 0.9731182795698924] |
| 0.0835 | 8.0 | 1520 | 0.1317 | [0.9736842105263158, 0.9731182795698924] |
| 0.0835 | 9.0 | 1710 | 0.1390 | [0.9738219895287958, 0.972972972972973] |
| 0.0835 | 10.0 | 1900 | 0.1299 | [0.9763779527559054, 0.9757412398921832] |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2