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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_grammar_task7_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_grammar_task7_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: 0.5050 |
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- Qwk: 0.6844 |
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- Mse: 0.4943 |
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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 | 1.0262 | 0.2825 | 1.0304 | |
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| No log | 0.6667 | 4 | 0.6994 | 0.6208 | 0.7254 | |
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| No log | 1.0 | 6 | 0.8144 | 0.4225 | 0.8374 | |
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| No log | 1.3333 | 8 | 0.6492 | 0.5810 | 0.6643 | |
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| No log | 1.6667 | 10 | 0.6577 | 0.4 | 0.6679 | |
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| No log | 2.0 | 12 | 0.5578 | 0.5957 | 0.5665 | |
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| No log | 2.3333 | 14 | 0.5481 | 0.6030 | 0.5532 | |
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| No log | 2.6667 | 16 | 0.4901 | 0.6290 | 0.4927 | |
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| No log | 3.0 | 18 | 0.4569 | 0.6780 | 0.4570 | |
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| No log | 3.3333 | 20 | 0.4974 | 0.6780 | 0.4927 | |
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| No log | 3.6667 | 22 | 0.5556 | 0.5326 | 0.5459 | |
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| No log | 4.0 | 24 | 0.5207 | 0.6370 | 0.5092 | |
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| No log | 4.3333 | 26 | 0.5155 | 0.6370 | 0.5024 | |
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| No log | 4.6667 | 28 | 0.5426 | 0.6370 | 0.5277 | |
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| No log | 5.0 | 30 | 0.5586 | 0.6416 | 0.5432 | |
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| No log | 5.3333 | 32 | 0.5285 | 0.6844 | 0.5150 | |
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| No log | 5.6667 | 34 | 0.4857 | 0.6844 | 0.4750 | |
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| No log | 6.0 | 36 | 0.4315 | 0.6780 | 0.4244 | |
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| No log | 6.3333 | 38 | 0.4483 | 0.6780 | 0.4406 | |
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| No log | 6.6667 | 40 | 0.5122 | 0.6844 | 0.5019 | |
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| No log | 7.0 | 42 | 0.5586 | 0.6283 | 0.5467 | |
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| No log | 7.3333 | 44 | 0.5142 | 0.6844 | 0.5032 | |
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| No log | 7.6667 | 46 | 0.4644 | 0.6844 | 0.4552 | |
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| No log | 8.0 | 48 | 0.4307 | 0.6780 | 0.4234 | |
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| No log | 8.3333 | 50 | 0.4377 | 0.6780 | 0.4300 | |
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| No log | 8.6667 | 52 | 0.4662 | 0.6780 | 0.4571 | |
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| No log | 9.0 | 54 | 0.4977 | 0.6844 | 0.4873 | |
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| No log | 9.3333 | 56 | 0.5069 | 0.6844 | 0.4961 | |
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| No log | 9.6667 | 58 | 0.5095 | 0.6844 | 0.4985 | |
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| No log | 10.0 | 60 | 0.5050 | 0.6844 | 0.4943 | |
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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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