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bert-base-uncased-with-preprocess-finetuned-emotion-3-epochs-5e-05-renamed
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: 0.1279
- Accuracy: 0.942
- F1: 0.9421
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: 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.5277 | 1.0 | 250 | 0.2037 | 0.926 | 0.9257 |
| 0.141 | 2.0 | 500 | 0.1352 | 0.9385 | 0.9387 |
| 0.0912 | 3.0 | 750 | 0.1279 | 0.942 | 0.9421 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3
