XLM-RoBERTa-xtreme-en
This model is a fine-tuned version of xlm-roberta-base on the xtreme_en dataset. It achieves the following results on the evaluation set:
- Loss: 0.2838
- Accuracy: 0.9109
- F1: 0.7544
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.6502 | 1.0 | 235 | 0.3328 | 0.8995 | 0.7251 |
| 0.3239 | 2.0 | 470 | 0.2897 | 0.9101 | 0.7473 |
| 0.2644 | 3.0 | 705 | 0.2838 | 0.9109 | 0.7544 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
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Evaluation results
- Accuracy on xtreme_enself-reported0.911
- F1 on xtreme_enself-reported0.754