uner_qaf_ara
This model is a fine-tuned version of xlm-roberta-large on the uner_qaf_ara dataset. It achieves the following results on the evaluation set:
- Loss: 0.1885
- Precision: 0.7241
- Recall: 0.7206
- F1: 0.7224
- Accuracy: 0.9548
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: 3e-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: 5.0
Training results
Framework versions
- Transformers 4.31.0
- Pytorch 1.10.1+cu113
- Datasets 2.14.4
- Tokenizers 0.13.3
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Evaluation results
- Precision on uner_qaf_aravalidation set self-reported0.724
- Recall on uner_qaf_aravalidation set self-reported0.721
- F1 on uner_qaf_aravalidation set self-reported0.722
- Accuracy on uner_qaf_aravalidation set self-reported0.955