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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_task2_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_grammar_task2_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: 1.2738 |
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- Qwk: 0.0491 |
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- Mse: 1.2508 |
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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 | 4.9005 | 0.0126 | 4.8502 | |
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| No log | 0.6667 | 4 | 2.4699 | 0.0387 | 2.4471 | |
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| No log | 1.0 | 6 | 1.4800 | -0.0982 | 1.4570 | |
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| No log | 1.3333 | 8 | 1.0496 | 0.0541 | 1.0294 | |
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| No log | 1.6667 | 10 | 1.2284 | 0.0 | 1.2139 | |
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| No log | 2.0 | 12 | 1.4327 | 0.0 | 1.4198 | |
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| No log | 2.3333 | 14 | 1.4042 | 0.0 | 1.3911 | |
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| No log | 2.6667 | 16 | 1.1140 | -0.0161 | 1.0974 | |
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| No log | 3.0 | 18 | 1.0138 | 0.1083 | 0.9870 | |
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| No log | 3.3333 | 20 | 1.0084 | 0.2200 | 0.9831 | |
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| No log | 3.6667 | 22 | 1.0806 | 0.0696 | 1.0592 | |
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| No log | 4.0 | 24 | 1.2446 | -0.1170 | 1.2246 | |
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| No log | 4.3333 | 26 | 1.4549 | -0.0960 | 1.4445 | |
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| No log | 4.6667 | 28 | 1.3332 | 0.0585 | 1.3205 | |
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| No log | 5.0 | 30 | 1.0953 | 0.0870 | 1.0641 | |
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| No log | 5.3333 | 32 | 1.0705 | 0.0616 | 1.0381 | |
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| No log | 5.6667 | 34 | 1.1503 | 0.1064 | 1.1300 | |
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| No log | 6.0 | 36 | 1.2818 | 0.0585 | 1.2670 | |
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| No log | 6.3333 | 38 | 1.3332 | -0.0161 | 1.3186 | |
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| No log | 6.6667 | 40 | 1.2686 | 0.0491 | 1.2516 | |
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| No log | 7.0 | 42 | 1.1870 | 0.0491 | 1.1658 | |
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| No log | 7.3333 | 44 | 1.1491 | 0.0491 | 1.1243 | |
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| No log | 7.6667 | 46 | 1.1946 | 0.0491 | 1.1709 | |
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| No log | 8.0 | 48 | 1.3196 | 0.0491 | 1.3003 | |
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| No log | 8.3333 | 50 | 1.3925 | 0.0541 | 1.3747 | |
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| No log | 8.6667 | 52 | 1.3818 | 0.0541 | 1.3633 | |
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| No log | 9.0 | 54 | 1.3491 | 0.0491 | 1.3293 | |
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| No log | 9.3333 | 56 | 1.3127 | 0.0491 | 1.2916 | |
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| No log | 9.6667 | 58 | 1.2864 | 0.0491 | 1.2640 | |
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| No log | 10.0 | 60 | 1.2738 | 0.0491 | 1.2508 | |
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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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