--- base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: arabert_cross_vocabulary_task2_fold3 results: [] --- # arabert_cross_vocabulary_task2_fold3 This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.7212 - Qwk: 0.7957 - Mse: 0.7212 ## 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: 1 ### Training results | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | |:-------------:|:------:|:----:|:---------------:|:------:|:------:| | No log | 0.0351 | 2 | 3.3323 | 0.0213 | 3.3323 | | No log | 0.0702 | 4 | 2.0333 | 0.1468 | 2.0333 | | No log | 0.1053 | 6 | 1.4923 | 0.3102 | 1.4923 | | No log | 0.1404 | 8 | 1.6734 | 0.3305 | 1.6734 | | No log | 0.1754 | 10 | 1.7352 | 0.2966 | 1.7352 | | No log | 0.2105 | 12 | 1.6360 | 0.2588 | 1.6360 | | No log | 0.2456 | 14 | 1.5076 | 0.2925 | 1.5076 | | No log | 0.2807 | 16 | 1.3433 | 0.3646 | 1.3433 | | No log | 0.3158 | 18 | 1.2343 | 0.4245 | 1.2343 | | No log | 0.3509 | 20 | 1.1517 | 0.5033 | 1.1517 | | No log | 0.3860 | 22 | 1.1391 | 0.6144 | 1.1391 | | No log | 0.4211 | 24 | 1.1438 | 0.6514 | 1.1438 | | No log | 0.4561 | 26 | 1.1808 | 0.6567 | 1.1808 | | No log | 0.4912 | 28 | 1.1197 | 0.7055 | 1.1197 | | No log | 0.5263 | 30 | 0.9660 | 0.7854 | 0.9660 | | No log | 0.5614 | 32 | 0.8893 | 0.7754 | 0.8893 | | No log | 0.5965 | 34 | 0.8546 | 0.7866 | 0.8546 | | No log | 0.6316 | 36 | 0.9013 | 0.7896 | 0.9013 | | No log | 0.6667 | 38 | 0.9216 | 0.8034 | 0.9216 | | No log | 0.7018 | 40 | 0.9057 | 0.7971 | 0.9057 | | No log | 0.7368 | 42 | 0.8462 | 0.7814 | 0.8462 | | No log | 0.7719 | 44 | 0.7936 | 0.7892 | 0.7936 | | No log | 0.8070 | 46 | 0.7517 | 0.8069 | 0.7517 | | No log | 0.8421 | 48 | 0.7133 | 0.7975 | 0.7133 | | No log | 0.8772 | 50 | 0.6939 | 0.7967 | 0.6939 | | No log | 0.9123 | 52 | 0.7043 | 0.7937 | 0.7043 | | No log | 0.9474 | 54 | 0.7171 | 0.7957 | 0.7171 | | No log | 0.9825 | 56 | 0.7212 | 0.7957 | 0.7212 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1