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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_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_development_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: 0.5447 |
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- Qwk: 0.4714 |
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- Mse: 0.5518 |
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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 | 3.5280 | -0.0028 | 3.6293 | |
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| No log | 0.6667 | 4 | 1.1366 | 0.0251 | 1.1880 | |
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| No log | 1.0 | 6 | 0.4107 | 0.0 | 0.4259 | |
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| No log | 1.3333 | 8 | 0.4662 | 0.1765 | 0.4494 | |
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| No log | 1.6667 | 10 | 0.3079 | 0.2075 | 0.3114 | |
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| No log | 2.0 | 12 | 0.2932 | 0.4101 | 0.2962 | |
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| No log | 2.3333 | 14 | 0.3202 | 0.1525 | 0.3155 | |
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| No log | 2.6667 | 16 | 0.4604 | 0.2410 | 0.4445 | |
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| No log | 3.0 | 18 | 0.3972 | 0.1765 | 0.3866 | |
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| No log | 3.3333 | 20 | 0.2887 | 0.1356 | 0.2966 | |
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| No log | 3.6667 | 22 | 0.3203 | 0.1907 | 0.3343 | |
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| No log | 4.0 | 24 | 0.3286 | 0.3453 | 0.3381 | |
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| No log | 4.3333 | 26 | 0.4544 | 0.1674 | 0.4506 | |
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| No log | 4.6667 | 28 | 0.5203 | 0.1674 | 0.5108 | |
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| No log | 5.0 | 30 | 0.4560 | 0.4453 | 0.4535 | |
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| No log | 5.3333 | 32 | 0.4023 | 0.4457 | 0.4083 | |
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| No log | 5.6667 | 34 | 0.3835 | 0.3453 | 0.3956 | |
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| No log | 6.0 | 36 | 0.4165 | 0.4231 | 0.4249 | |
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| No log | 6.3333 | 38 | 0.5295 | 0.4152 | 0.5286 | |
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| No log | 6.6667 | 40 | 0.6129 | 0.2759 | 0.6063 | |
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| No log | 7.0 | 42 | 0.6169 | 0.2759 | 0.6109 | |
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| No log | 7.3333 | 44 | 0.5387 | 0.3971 | 0.5393 | |
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| No log | 7.6667 | 46 | 0.4830 | 0.3913 | 0.4895 | |
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| No log | 8.0 | 48 | 0.4890 | 0.3695 | 0.4962 | |
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| No log | 8.3333 | 50 | 0.5286 | 0.4714 | 0.5334 | |
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| No log | 8.6667 | 52 | 0.5656 | 0.3971 | 0.5690 | |
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| No log | 9.0 | 54 | 0.5673 | 0.4714 | 0.5716 | |
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| No log | 9.3333 | 56 | 0.5533 | 0.4714 | 0.5593 | |
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| No log | 9.6667 | 58 | 0.5477 | 0.4714 | 0.5545 | |
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| No log | 10.0 | 60 | 0.5447 | 0.4714 | 0.5518 | |
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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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