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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_mechanics_task1_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_mechanics_task1_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: 0.5507 |
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- Qwk: 0.4324 |
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- Mse: 0.5505 |
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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 | 4.9042 | 0.0 | 4.9234 | |
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| No log | 0.6667 | 4 | 2.0020 | -0.0299 | 2.0282 | |
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| No log | 1.0 | 6 | 1.2914 | 0.0769 | 1.3136 | |
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| No log | 1.3333 | 8 | 1.0020 | 0.0500 | 1.0184 | |
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| No log | 1.6667 | 10 | 0.7738 | 0.125 | 0.7839 | |
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| No log | 2.0 | 12 | 0.8249 | 0.2105 | 0.8327 | |
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| No log | 2.3333 | 14 | 1.0118 | 0.0851 | 1.0228 | |
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| No log | 2.6667 | 16 | 0.7586 | 0.1905 | 0.7651 | |
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| No log | 3.0 | 18 | 0.4977 | 0.375 | 0.5025 | |
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| No log | 3.3333 | 20 | 0.5065 | 0.3429 | 0.5107 | |
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| No log | 3.6667 | 22 | 0.5186 | 0.4118 | 0.5205 | |
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| No log | 4.0 | 24 | 0.7202 | 0.2564 | 0.7199 | |
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| No log | 4.3333 | 26 | 0.6120 | 0.3889 | 0.6080 | |
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| No log | 4.6667 | 28 | 0.5684 | 0.3784 | 0.5637 | |
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| No log | 5.0 | 30 | 0.5531 | 0.3889 | 0.5482 | |
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| No log | 5.3333 | 32 | 0.6399 | 0.3784 | 0.6320 | |
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| No log | 5.6667 | 34 | 0.8218 | 0.2632 | 0.8129 | |
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| No log | 6.0 | 36 | 0.8057 | 0.2632 | 0.7976 | |
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| No log | 6.3333 | 38 | 0.6262 | 0.3784 | 0.6183 | |
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| No log | 6.6667 | 40 | 0.6028 | 0.3889 | 0.5950 | |
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| No log | 7.0 | 42 | 0.6011 | 0.3889 | 0.5943 | |
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| No log | 7.3333 | 44 | 0.6488 | 0.3158 | 0.6438 | |
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| No log | 7.6667 | 46 | 0.5939 | 0.3158 | 0.5907 | |
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| No log | 8.0 | 48 | 0.5456 | 0.4324 | 0.5440 | |
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| No log | 8.3333 | 50 | 0.5191 | 0.4324 | 0.5183 | |
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| No log | 8.6667 | 52 | 0.4890 | 0.4324 | 0.4889 | |
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| No log | 9.0 | 54 | 0.4994 | 0.4324 | 0.4996 | |
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| No log | 9.3333 | 56 | 0.5265 | 0.4324 | 0.5267 | |
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| No log | 9.6667 | 58 | 0.5469 | 0.4324 | 0.5468 | |
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| No log | 10.0 | 60 | 0.5507 | 0.4324 | 0.5505 | |
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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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