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--- |
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base_model: aubmindlab/bert-base-arabertv02 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: arabert_cross_vocabulary_task2_fold3 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# arabert_cross_vocabulary_task2_fold3 |
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This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7212 |
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- Qwk: 0.7957 |
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- Mse: 0.7212 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | |
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|:-------------:|:------:|:----:|:---------------:|:------:|:------:| |
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| No log | 0.0351 | 2 | 3.3323 | 0.0213 | 3.3323 | |
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| No log | 0.0702 | 4 | 2.0333 | 0.1468 | 2.0333 | |
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| No log | 0.1053 | 6 | 1.4923 | 0.3102 | 1.4923 | |
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| No log | 0.1404 | 8 | 1.6734 | 0.3305 | 1.6734 | |
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| No log | 0.1754 | 10 | 1.7352 | 0.2966 | 1.7352 | |
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| No log | 0.2105 | 12 | 1.6360 | 0.2588 | 1.6360 | |
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| No log | 0.2456 | 14 | 1.5076 | 0.2925 | 1.5076 | |
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| No log | 0.2807 | 16 | 1.3433 | 0.3646 | 1.3433 | |
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| No log | 0.3158 | 18 | 1.2343 | 0.4245 | 1.2343 | |
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| No log | 0.3509 | 20 | 1.1517 | 0.5033 | 1.1517 | |
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| No log | 0.3860 | 22 | 1.1391 | 0.6144 | 1.1391 | |
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| No log | 0.4211 | 24 | 1.1438 | 0.6514 | 1.1438 | |
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| No log | 0.4561 | 26 | 1.1808 | 0.6567 | 1.1808 | |
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| No log | 0.4912 | 28 | 1.1197 | 0.7055 | 1.1197 | |
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| No log | 0.5263 | 30 | 0.9660 | 0.7854 | 0.9660 | |
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| No log | 0.5614 | 32 | 0.8893 | 0.7754 | 0.8893 | |
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| No log | 0.5965 | 34 | 0.8546 | 0.7866 | 0.8546 | |
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| No log | 0.6316 | 36 | 0.9013 | 0.7896 | 0.9013 | |
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| No log | 0.6667 | 38 | 0.9216 | 0.8034 | 0.9216 | |
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| No log | 0.7018 | 40 | 0.9057 | 0.7971 | 0.9057 | |
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| No log | 0.7368 | 42 | 0.8462 | 0.7814 | 0.8462 | |
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| No log | 0.7719 | 44 | 0.7936 | 0.7892 | 0.7936 | |
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| No log | 0.8070 | 46 | 0.7517 | 0.8069 | 0.7517 | |
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| No log | 0.8421 | 48 | 0.7133 | 0.7975 | 0.7133 | |
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| No log | 0.8772 | 50 | 0.6939 | 0.7967 | 0.6939 | |
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| No log | 0.9123 | 52 | 0.7043 | 0.7937 | 0.7043 | |
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| No log | 0.9474 | 54 | 0.7171 | 0.7957 | 0.7171 | |
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| No log | 0.9825 | 56 | 0.7212 | 0.7957 | 0.7212 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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