XLM_Lexical_CITA_15k
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5557
- Accuracy: 0.8093
- F1: 0.8034
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: Use adamw_torch 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 |
---|---|---|---|---|---|
0.557 | 1.0 | 375 | 0.4996 | 0.7807 | 0.7648 |
0.4775 | 2.0 | 750 | 0.4805 | 0.793 | 0.7770 |
0.4323 | 3.0 | 1125 | 0.4718 | 0.7993 | 0.7821 |
0.3898 | 4.0 | 1500 | 0.4642 | 0.8 | 0.7818 |
0.3523 | 5.0 | 1875 | 0.4663 | 0.8047 | 0.7995 |
0.3214 | 6.0 | 2250 | 0.5082 | 0.8133 | 0.8085 |
0.2928 | 7.0 | 2625 | 0.5124 | 0.8103 | 0.8039 |
0.2685 | 8.0 | 3000 | 0.5304 | 0.8137 | 0.8081 |
0.2479 | 9.0 | 3375 | 0.5597 | 0.8077 | 0.8033 |
0.2391 | 10.0 | 3750 | 0.5557 | 0.8093 | 0.8034 |
Framework versions
- Transformers 4.48.0
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.21.0
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Base model
FacebookAI/xlm-roberta-base