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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_development_task1_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_baseline_development_task1_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: 0.5902 |
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- Qwk: 0.5813 |
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- Mse: 0.5907 |
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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 | 4.3908 | -0.0120 | 4.3758 | |
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| No log | 0.6667 | 4 | 1.6600 | 0.1250 | 1.6454 | |
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| No log | 1.0 | 6 | 0.7866 | 0.1857 | 0.7857 | |
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| No log | 1.3333 | 8 | 0.8027 | 0.3213 | 0.8042 | |
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| No log | 1.6667 | 10 | 0.7663 | 0.4436 | 0.7681 | |
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| No log | 2.0 | 12 | 0.6285 | 0.5382 | 0.6319 | |
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| No log | 2.3333 | 14 | 0.5709 | 0.5522 | 0.5784 | |
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| No log | 2.6667 | 16 | 0.6087 | 0.5551 | 0.6118 | |
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| No log | 3.0 | 18 | 0.6828 | 0.5551 | 0.6824 | |
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| No log | 3.3333 | 20 | 0.7735 | 0.5415 | 0.7740 | |
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| No log | 3.6667 | 22 | 0.6982 | 0.5682 | 0.6989 | |
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| No log | 4.0 | 24 | 0.7101 | 0.5682 | 0.7116 | |
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| No log | 4.3333 | 26 | 0.6932 | 0.5682 | 0.6950 | |
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| No log | 4.6667 | 28 | 0.6914 | 0.5682 | 0.6938 | |
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| No log | 5.0 | 30 | 0.6162 | 0.5477 | 0.6186 | |
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| No log | 5.3333 | 32 | 0.5655 | 0.5477 | 0.5678 | |
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| No log | 5.6667 | 34 | 0.5450 | 0.5445 | 0.5471 | |
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| No log | 6.0 | 36 | 0.5674 | 0.5477 | 0.5701 | |
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| No log | 6.3333 | 38 | 0.6194 | 0.5314 | 0.6234 | |
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| No log | 6.6667 | 40 | 0.5904 | 0.5477 | 0.5926 | |
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| No log | 7.0 | 42 | 0.5761 | 0.5445 | 0.5768 | |
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| No log | 7.3333 | 44 | 0.5947 | 0.5813 | 0.5951 | |
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| No log | 7.6667 | 46 | 0.6094 | 0.5825 | 0.6096 | |
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| No log | 8.0 | 48 | 0.6288 | 0.5995 | 0.6294 | |
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| No log | 8.3333 | 50 | 0.6317 | 0.5269 | 0.6325 | |
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| No log | 8.6667 | 52 | 0.6245 | 0.5995 | 0.6251 | |
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| No log | 9.0 | 54 | 0.6067 | 0.5825 | 0.6071 | |
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| No log | 9.3333 | 56 | 0.5975 | 0.5813 | 0.5979 | |
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| No log | 9.6667 | 58 | 0.5916 | 0.5813 | 0.5921 | |
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| No log | 10.0 | 60 | 0.5902 | 0.5813 | 0.5907 | |
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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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