bert-base-cased-finetuned-emotion
This model is a fine-tuned version of bert-base-cased on the emotion dataset. It achieves the following results on the evaluation set:
- Loss: 0.1342
- F1: 0.9365
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: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.7357 | 1.0 | 250 | 0.2318 | 0.9224 |
| 0.1758 | 2.0 | 500 | 0.1679 | 0.9349 |
| 0.1228 | 3.0 | 750 | 0.1385 | 0.9382 |
| 0.0961 | 4.0 | 1000 | 0.1452 | 0.9340 |
| 0.0805 | 5.0 | 1250 | 0.1342 | 0.9365 |
Framework versions
- Transformers 4.12.5
- Pytorch 1.10.0+cu111
- Datasets 1.16.1
- Tokenizers 0.10.3
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