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distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0748
- Accuracy: 1.0
- F1: 1.0
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 2.1253 | 1.0 | 21 | 1.8182 | 0.9391 | 0.9260 |
| 1.5009 | 2.0 | 42 | 1.0205 | 0.9652 | 0.9501 |
| 0.9143 | 3.0 | 63 | 0.5262 | 0.9957 | 0.9956 |
| 0.5215 | 4.0 | 84 | 0.2827 | 1.0 | 1.0 |
| 0.3069 | 5.0 | 105 | 0.1716 | 1.0 | 1.0 |
| 0.199 | 6.0 | 126 | 0.1194 | 1.0 | 1.0 |
| 0.147 | 7.0 | 147 | 0.0955 | 1.0 | 1.0 |
| 0.1229 | 8.0 | 168 | 0.0830 | 1.0 | 1.0 |
| 0.1076 | 9.0 | 189 | 0.0768 | 1.0 | 1.0 |
| 0.1002 | 10.0 | 210 | 0.0748 | 1.0 | 1.0 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
