distilbert-base-uncased-fine-tuned-emotions
This model is a fine-tuned version of distilbert-base-uncased on the emotion dataset. It achieves the following results on the evaluation set:
- Loss: 0.1377
- Accuracy: 0.9335
- F1 Score: 0.9338
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: 0.0002
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score |
|---|---|---|---|---|---|
| 0.478 | 1.0 | 125 | 0.1852 | 0.931 | 0.9309 |
| 0.1285 | 2.0 | 250 | 0.1377 | 0.9335 | 0.9338 |
Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.8.1+cu101
- Datasets 2.7.1
- Tokenizers 0.10.1
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