multipride_umberto_sent_label
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: 0.2326
- Accuracy: 0.9325
- Precision: 0.8816
- Recall: 0.9090
- F1: 0.8943
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 |
|---|---|---|---|---|---|---|---|
| 0.3403 | 1.0 | 95 | 0.2707 | 0.9141 | 0.9285 | 0.7865 | 0.8346 |
| 0.1875 | 2.0 | 190 | 0.2311 | 0.9202 | 0.8902 | 0.8397 | 0.8618 |
| 0.1657 | 3.0 | 285 | 0.2787 | 0.9325 | 0.8736 | 0.9337 | 0.8989 |
| 0.1117 | 4.0 | 380 | 0.2278 | 0.9325 | 0.9026 | 0.8719 | 0.8862 |
| 0.0448 | 5.0 | 475 | 0.2326 | 0.9325 | 0.8816 | 0.9090 | 0.8943 |
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_sent_label
Base model
Musixmatch/umberto-commoncrawl-cased-v1