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distilbert-base-uncased-finetuned-emotion-lr-0.0006-wd-0003
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: 0.4198
- Accuracy: 0.8875
- F1: 0.8889
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: 0.0006
- 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.1911 | 1.0 | 125 | 0.6098 | 0.808 | 0.7921 |
| 0.4819 | 2.0 | 250 | 0.4198 | 0.8875 | 0.8889 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.10.0
- Datasets 2.6.1
- Tokenizers 0.13.1
