multipride_umberto
This model is a fine-tuned version of Musixmatch/umberto-commoncrawl-cased-v1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3664
- Accuracy: 0.9202
- Precision: 0.9015
- Recall: 0.8273
- F1: 0.8578
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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.3334 | 1.0 | 95 | 0.3002 | 0.9080 | 0.9239 | 0.7704 | 0.8199 |
| 0.2216 | 2.0 | 190 | 0.2308 | 0.9141 | 0.9285 | 0.7865 | 0.8346 |
| 0.1196 | 3.0 | 285 | 0.3063 | 0.9202 | 0.8593 | 0.9014 | 0.8779 |
| 0.0925 | 4.0 | 380 | 0.3114 | 0.9264 | 0.8965 | 0.8558 | 0.8742 |
| 0.0292 | 5.0 | 475 | 0.3664 | 0.9202 | 0.9015 | 0.8273 | 0.8578 |
Framework versions
- Transformers 4.57.2
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
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Model tree for grexit-d/multipride_umberto
Base model
Musixmatch/umberto-commoncrawl-cased-v1