distilbert-base-multilingual-cased-finetuned-emotion
This model is a fine-tuned version of distilbert/distilbert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1933
- Accuracy: 0.9325
- F1: 0.9327
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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.0673 | 1.0 | 250 | 0.4498 | 0.866 | 0.8649 |
| 0.3100 | 2.0 | 500 | 0.2474 | 0.9135 | 0.9133 |
| 0.1818 | 3.0 | 750 | 0.2131 | 0.921 | 0.9219 |
| 0.1398 | 4.0 | 1000 | 0.1877 | 0.929 | 0.9295 |
| 0.1082 | 5.0 | 1250 | 0.1874 | 0.9275 | 0.9277 |
| 0.0915 | 6.0 | 1500 | 0.1894 | 0.931 | 0.9313 |
| 0.0790 | 7.0 | 1750 | 0.1910 | 0.931 | 0.9308 |
| 0.0678 | 8.0 | 2000 | 0.1939 | 0.931 | 0.9312 |
| 0.0574 | 9.0 | 2250 | 0.1976 | 0.93 | 0.9303 |
| 0.0511 | 10.0 | 2500 | 0.1933 | 0.9325 | 0.9327 |
Framework versions
- Transformers 5.12.1
- Pytorch 2.12.0
- Datasets 5.0.0
- Tokenizers 0.22.2