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xlm-roberta-base-Mixed-origin
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0048
- Accuracy: 0.7973
- F1: 0.7946
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 |
|---|---|---|---|---|---|
| 0.7588 | 1.0 | 166 | 0.5565 | 0.7716 | 0.7373 |
| 0.5376 | 2.0 | 332 | 0.5383 | 0.7867 | 0.7776 |
| 0.4487 | 3.0 | 498 | 0.5118 | 0.7973 | 0.7899 |
| 0.3686 | 4.0 | 664 | 0.6558 | 0.7988 | 0.7859 |
| 0.3079 | 5.0 | 830 | 0.7122 | 0.8018 | 0.7914 |
| 0.2486 | 6.0 | 996 | 0.7233 | 0.8048 | 0.8041 |
| 0.2222 | 7.0 | 1162 | 0.8130 | 0.8018 | 0.8014 |
| 0.1815 | 8.0 | 1328 | 0.8598 | 0.8003 | 0.7997 |
| 0.1593 | 9.0 | 1494 | 0.9768 | 0.8033 | 0.7994 |
| 0.1466 | 10.0 | 1660 | 1.0048 | 0.7973 | 0.7946 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
