XLM_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: 0.5214
- Accuracy: 0.816
- F1: 0.8109
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: cosine_with_restarts
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.5803 | 1.0 | 375 | 0.5200 | 0.7667 | 0.7542 |
0.4983 | 2.0 | 750 | 0.5083 | 0.7903 | 0.7755 |
0.4435 | 3.0 | 1125 | 0.4712 | 0.7983 | 0.7927 |
0.3978 | 4.0 | 1500 | 0.4714 | 0.7987 | 0.7829 |
0.3602 | 5.0 | 1875 | 0.4740 | 0.8117 | 0.8084 |
0.3255 | 6.0 | 2250 | 0.4837 | 0.816 | 0.8111 |
0.2928 | 7.0 | 2625 | 0.5151 | 0.815 | 0.8082 |
0.2791 | 8.0 | 3000 | 0.5073 | 0.815 | 0.8083 |
0.2672 | 9.0 | 3375 | 0.5156 | 0.8167 | 0.8113 |
0.2614 | 10.0 | 3750 | 0.5214 | 0.816 | 0.8109 |
Framework versions
- Transformers 4.48.0
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.21.0
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Model tree for phunganhsang/XLM_CITA_15k
Base model
FacebookAI/xlm-roberta-base