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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_task1_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_task1_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: 0.6330 |
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- Qwk: 0.8116 |
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- Mse: 0.6330 |
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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 | 3.3598 | 0.0190 | 3.3598 | |
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| No log | 0.0702 | 4 | 2.4609 | 0.1303 | 2.4609 | |
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| No log | 0.1053 | 6 | 1.4030 | 0.3203 | 1.4030 | |
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| No log | 0.1404 | 8 | 1.5047 | 0.4056 | 1.5047 | |
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| No log | 0.1754 | 10 | 1.6841 | 0.5201 | 1.6841 | |
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| No log | 0.2105 | 12 | 1.2050 | 0.4844 | 1.2050 | |
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| No log | 0.2456 | 14 | 1.0340 | 0.4610 | 1.0340 | |
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| No log | 0.2807 | 16 | 0.9004 | 0.5199 | 0.9004 | |
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| No log | 0.3158 | 18 | 0.8944 | 0.7299 | 0.8944 | |
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| No log | 0.3509 | 20 | 0.7872 | 0.7550 | 0.7872 | |
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| No log | 0.3860 | 22 | 0.6647 | 0.7227 | 0.6647 | |
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| No log | 0.4211 | 24 | 0.6390 | 0.7315 | 0.6390 | |
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| No log | 0.4561 | 26 | 0.6404 | 0.7837 | 0.6404 | |
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| No log | 0.4912 | 28 | 0.8258 | 0.8035 | 0.8258 | |
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| No log | 0.5263 | 30 | 0.8849 | 0.8022 | 0.8849 | |
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| No log | 0.5614 | 32 | 0.7788 | 0.8146 | 0.7788 | |
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| No log | 0.5965 | 34 | 0.6878 | 0.7879 | 0.6878 | |
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| No log | 0.6316 | 36 | 0.6812 | 0.7867 | 0.6812 | |
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| No log | 0.6667 | 38 | 0.7533 | 0.8236 | 0.7533 | |
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| No log | 0.7018 | 40 | 0.8468 | 0.8151 | 0.8468 | |
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| No log | 0.7368 | 42 | 0.8501 | 0.8191 | 0.8501 | |
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| No log | 0.7719 | 44 | 0.8291 | 0.8174 | 0.8291 | |
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| No log | 0.8070 | 46 | 0.7683 | 0.8084 | 0.7683 | |
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| No log | 0.8421 | 48 | 0.7140 | 0.8190 | 0.7140 | |
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| No log | 0.8772 | 50 | 0.6780 | 0.8204 | 0.6780 | |
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| No log | 0.9123 | 52 | 0.6546 | 0.8181 | 0.6546 | |
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| No log | 0.9474 | 54 | 0.6399 | 0.8097 | 0.6399 | |
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| No log | 0.9825 | 56 | 0.6330 | 0.8116 | 0.6330 | |
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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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