slurp-intent_baseline-xlm_r-en
This model is a fine-tuned version of xlm-roberta-base on an SLURP dataset.
It achieves the following results on the test set:
- Loss: 0.68222
- Accuracy: 0.8746
- F1: 0.8746
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: 16
- eval_batch_size: 16
- 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 |
|---|---|---|---|---|---|
| 2.9687 | 1.0 | 720 | 1.3267 | 0.6955 | 0.6955 |
| 1.4534 | 2.0 | 1440 | 0.8053 | 0.8219 | 0.8219 |
| 0.6775 | 3.0 | 2160 | 0.6912 | 0.8421 | 0.8421 |
| 0.5624 | 4.0 | 2880 | 0.6377 | 0.8623 | 0.8623 |
| 0.3756 | 5.0 | 3600 | 0.6188 | 0.8746 | 0.8746 |
| 0.3346 | 6.0 | 4320 | 0.6548 | 0.8711 | 0.8711 |
| 0.2541 | 7.0 | 5040 | 0.6618 | 0.8751 | 0.8751 |
| 0.2243 | 8.0 | 5760 | 0.6662 | 0.8780 | 0.8780 |
| 0.212 | 9.0 | 6480 | 0.6673 | 0.8810 | 0.8810 |
| 0.1664 | 10.0 | 7200 | 0.6783 | 0.8810 | 0.8810 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3