test_classifier
This model is a fine-tuned version of j-hartmann/emotion-english-distilroberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8668
- Accuracy: 0.7337
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: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7506 | 1.0 | 587 | 0.8760 | 0.7145 |
| 0.6506 | 2.0 | 1174 | 0.8192 | 0.7303 |
| 0.5242 | 3.0 | 1761 | 0.8668 | 0.7337 |
Framework versions
- Transformers 4.22.2
- Pytorch 1.12.1+cu102
- Datasets 2.5.2
- Tokenizers 0.12.1
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