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distilbert-base-uncased_emotion_ft_0416
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: 0.1487
- Accuracy: 0.937
- F1: 0.9371
- Precision: 0.9127
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision |
---|---|---|---|---|---|---|
0.7892 | 1.0 | 250 | 0.2543 | 0.9235 | 0.9221 | 0.9172 |
0.2039 | 2.0 | 500 | 0.1742 | 0.9275 | 0.9276 | 0.9069 |
0.1371 | 3.0 | 750 | 0.1521 | 0.9375 | 0.9378 | 0.9104 |
0.1108 | 4.0 | 1000 | 0.1487 | 0.937 | 0.9371 | 0.9127 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3