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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_task3_fold0 |
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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_task3_fold0 |
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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: 0.6808 |
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- Qwk: 0.5680 |
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- Mse: 0.6804 |
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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 | 0.0323 | 2 | 4.4744 | -0.0256 | 4.4706 | |
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| No log | 0.0645 | 4 | 2.3045 | 0.0249 | 2.3004 | |
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| No log | 0.0968 | 6 | 1.2805 | 0.1391 | 1.2779 | |
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| No log | 0.1290 | 8 | 1.0125 | 0.1335 | 1.0109 | |
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| No log | 0.1613 | 10 | 1.0701 | 0.1914 | 1.0686 | |
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| No log | 0.1935 | 12 | 1.2785 | 0.2037 | 1.2768 | |
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| No log | 0.2258 | 14 | 1.2274 | 0.2479 | 1.2257 | |
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| No log | 0.2581 | 16 | 1.0548 | 0.3135 | 1.0534 | |
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| No log | 0.2903 | 18 | 0.9068 | 0.4200 | 0.9058 | |
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| No log | 0.3226 | 20 | 0.8042 | 0.4719 | 0.8035 | |
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| No log | 0.3548 | 22 | 0.7409 | 0.5318 | 0.7404 | |
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| No log | 0.3871 | 24 | 0.7832 | 0.5356 | 0.7827 | |
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| No log | 0.4194 | 26 | 0.8927 | 0.5031 | 0.8924 | |
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| No log | 0.4516 | 28 | 1.1506 | 0.4441 | 1.1505 | |
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| No log | 0.4839 | 30 | 1.4202 | 0.3909 | 1.4201 | |
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| No log | 0.5161 | 32 | 1.1610 | 0.4441 | 1.1608 | |
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| No log | 0.5484 | 34 | 0.8093 | 0.5444 | 0.8088 | |
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| No log | 0.5806 | 36 | 0.6806 | 0.5981 | 0.6803 | |
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| No log | 0.6129 | 38 | 0.6480 | 0.5752 | 0.6477 | |
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| No log | 0.6452 | 40 | 0.6549 | 0.5691 | 0.6546 | |
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| No log | 0.6774 | 42 | 0.7025 | 0.5317 | 0.7021 | |
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| No log | 0.7097 | 44 | 0.7321 | 0.5105 | 0.7317 | |
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| No log | 0.7419 | 46 | 0.7334 | 0.5066 | 0.7330 | |
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| No log | 0.7742 | 48 | 0.7273 | 0.5221 | 0.7269 | |
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| No log | 0.8065 | 50 | 0.7075 | 0.5309 | 0.7071 | |
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| No log | 0.8387 | 52 | 0.6855 | 0.5374 | 0.6852 | |
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| No log | 0.8710 | 54 | 0.6736 | 0.5635 | 0.6733 | |
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| No log | 0.9032 | 56 | 0.6784 | 0.5680 | 0.6781 | |
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| No log | 0.9355 | 58 | 0.6858 | 0.5657 | 0.6855 | |
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| No log | 0.9677 | 60 | 0.6828 | 0.5669 | 0.6825 | |
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| No log | 1.0 | 62 | 0.6808 | 0.5680 | 0.6804 | |
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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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