bert-base-emotion-intent
This model is a fine-tuned version of bert-base-uncased on the emotion dataset. It achieves the following results on the evaluation set:
- Loss: 0.1952
- Accuracy: 0.9385
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 33
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4058 | 1.0 | 1000 | 0.2421 | 0.9265 |
| 0.1541 | 2.0 | 2000 | 0.1952 | 0.9385 |
| 0.1279 | 3.0 | 3000 | 0.1807 | 0.9345 |
| 0.1069 | 4.0 | 4000 | 0.2292 | 0.9365 |
| 0.081 | 5.0 | 5000 | 0.3315 | 0.936 |
Framework versions
- Transformers 4.22.1
- Pytorch 1.12.1+cu113
- Datasets 2.5.1
- Tokenizers 0.12.1
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