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distilbert-base-uncased_emotion_ft_learn2pro
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: 0.1427
- Accuracy: 0.937
- F1: 0.9373
- Precision: 0.9097
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 |
---|---|---|---|---|---|---|
0.7939 | 1.0 | 250 | 0.2551 | 0.9115 | 0.9095 | 0.8923 |
0.2063 | 2.0 | 500 | 0.1629 | 0.931 | 0.9310 | 0.9116 |
0.1384 | 3.0 | 750 | 0.1491 | 0.9375 | 0.9380 | 0.9073 |
0.1099 | 4.0 | 1000 | 0.1427 | 0.937 | 0.9373 | 0.9097 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3