distilbert-base-uncased-finetuned-emotion
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: 0.1891
- Accuracy: 0.9405
- F1: 0.9405
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: 16
- eval_batch_size: 16
- 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 |
|---|---|---|---|---|---|
| 0.1344 | 1.0 | 1000 | 0.1760 | 0.933 | 0.9331 |
| 0.0823 | 2.0 | 2000 | 0.1891 | 0.9405 | 0.9405 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0.post202
- Datasets 2.3.2
- Tokenizers 0.11.0
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Dataset used to train michauhl/distilbert-base-uncased-finetuned-emotion
Evaluation results
- Accuracy on emotionself-reported0.941
- F1 on emotionself-reported0.940