irony_classification_single_label_base
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: 0.9822
- Accuracy: 0.6227
- F1: 0.5853
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: 8
- eval_batch_size: 8
- 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 | Accuracy | F1 |
---|---|---|---|---|---|
0.9554 | 1.0 | 718 | 0.8483 | 0.6247 | 0.5794 |
0.6941 | 2.0 | 1436 | 0.9822 | 0.6227 | 0.5853 |
0.3184 | 3.0 | 2154 | 1.5308 | 0.6206 | 0.5835 |
0.2401 | 4.0 | 2872 | 2.0444 | 0.6093 | 0.5714 |
0.1284 | 5.0 | 3590 | 2.1603 | 0.6124 | 0.5643 |
0.0646 | 6.0 | 4308 | 2.3836 | 0.6041 | 0.5571 |
0.0362 | 7.0 | 5026 | 2.5046 | 0.6268 | 0.5635 |
0.0232 | 8.0 | 5744 | 2.6831 | 0.6072 | 0.5534 |
0.024 | 9.0 | 6462 | 2.7345 | 0.6165 | 0.5546 |
0.0084 | 10.0 | 7180 | 2.7679 | 0.6144 | 0.5616 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0+cu118
- Datasets 2.19.0
- Tokenizers 0.19.1
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