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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_baseline_vocabulary_task2_fold1 |
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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_baseline_vocabulary_task2_fold1 |
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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: 0.5031 |
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- Qwk: 0.5714 |
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- Mse: 0.5016 |
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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: 10 |
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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 | 0.3333 | 2 | 4.1484 | 0.0038 | 4.1936 | |
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| No log | 0.6667 | 4 | 1.4862 | 0.0810 | 1.5068 | |
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| No log | 1.0 | 6 | 0.7072 | 0.0 | 0.7085 | |
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| No log | 1.3333 | 8 | 0.5919 | 0.0 | 0.5727 | |
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| No log | 1.6667 | 10 | 0.7019 | 0.0 | 0.6799 | |
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| No log | 2.0 | 12 | 0.4359 | 0.2329 | 0.4303 | |
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| No log | 2.3333 | 14 | 0.4598 | 0.1250 | 0.4561 | |
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| No log | 2.6667 | 16 | 0.4071 | 0.5145 | 0.3971 | |
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| No log | 3.0 | 18 | 0.5588 | 0.1732 | 0.5418 | |
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| No log | 3.3333 | 20 | 0.6199 | 0.1732 | 0.6015 | |
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| No log | 3.6667 | 22 | 0.4817 | 0.4400 | 0.4688 | |
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| No log | 4.0 | 24 | 0.3891 | 0.2959 | 0.3830 | |
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| No log | 4.3333 | 26 | 0.4411 | 0.1777 | 0.4351 | |
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| No log | 4.6667 | 28 | 0.4012 | 0.3959 | 0.3959 | |
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| No log | 5.0 | 30 | 0.4347 | 0.4765 | 0.4291 | |
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| No log | 5.3333 | 32 | 0.6742 | 0.4970 | 0.6581 | |
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| No log | 5.6667 | 34 | 0.7767 | 0.5273 | 0.7561 | |
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| No log | 6.0 | 36 | 0.7418 | 0.5836 | 0.7250 | |
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| No log | 6.3333 | 38 | 0.6070 | 0.4706 | 0.5993 | |
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| No log | 6.6667 | 40 | 0.4832 | 0.5714 | 0.4805 | |
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| No log | 7.0 | 42 | 0.4590 | 0.6196 | 0.4554 | |
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| No log | 7.3333 | 44 | 0.4604 | 0.6196 | 0.4573 | |
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| No log | 7.6667 | 46 | 0.4911 | 0.5714 | 0.4888 | |
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| No log | 8.0 | 48 | 0.5594 | 0.4415 | 0.5549 | |
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| No log | 8.3333 | 50 | 0.5973 | 0.5215 | 0.5910 | |
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| No log | 8.6667 | 52 | 0.5945 | 0.4415 | 0.5886 | |
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| No log | 9.0 | 54 | 0.5659 | 0.4415 | 0.5617 | |
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| No log | 9.3333 | 56 | 0.5343 | 0.5215 | 0.5317 | |
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| No log | 9.6667 | 58 | 0.5134 | 0.4976 | 0.5116 | |
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| No log | 10.0 | 60 | 0.5031 | 0.5714 | 0.5016 | |
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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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