fedcsis_translated-intent_baseline-xlm_r-pl
This model is a fine-tuned version of xlm-roberta-base on the leyzer-fedcsis-translated dataset.
Results on untranslated test set:
- Accuracy: 0.8769
It achieves the following results on the evaluation set:
- Loss: 0.5478
- Accuracy: 0.8769
- F1: 0.8769
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 |
|---|---|---|---|---|---|
| 3.505 | 1.0 | 814 | 1.8819 | 0.5979 | 0.5979 |
| 1.5056 | 2.0 | 1628 | 1.1033 | 0.7611 | 0.7611 |
| 1.0892 | 3.0 | 2442 | 0.7402 | 0.8470 | 0.8470 |
| 0.648 | 4.0 | 3256 | 0.5263 | 0.8902 | 0.8902 |
| 0.423 | 5.0 | 4070 | 0.4253 | 0.9152 | 0.9152 |
| 0.3429 | 6.0 | 4884 | 0.3654 | 0.9194 | 0.9194 |
| 0.2464 | 7.0 | 5698 | 0.3213 | 0.9273 | 0.9273 |
| 0.1873 | 8.0 | 6512 | 0.3065 | 0.9328 | 0.9328 |
| 0.1666 | 9.0 | 7326 | 0.3046 | 0.9345 | 0.9345 |
| 0.1459 | 10.0 | 8140 | 0.2911 | 0.9370 | 0.9370 |
Framework versions
- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
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