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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_organization_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_organization_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: 0.4765 |
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- Qwk: 0.5051 |
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- Mse: 0.4812 |
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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 | 3.4785 | 0.0139 | 3.4271 | |
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| No log | 0.6667 | 4 | 1.3527 | 0.0988 | 1.3438 | |
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| No log | 1.0 | 6 | 0.9762 | 0.0466 | 0.9710 | |
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| No log | 1.3333 | 8 | 0.5845 | 0.3068 | 0.5906 | |
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| No log | 1.6667 | 10 | 0.6355 | 0.4901 | 0.6479 | |
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| No log | 2.0 | 12 | 0.6002 | 0.4901 | 0.6080 | |
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| No log | 2.3333 | 14 | 0.5521 | 0.3591 | 0.5519 | |
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| No log | 2.6667 | 16 | 0.5671 | 0.5312 | 0.5733 | |
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| No log | 3.0 | 18 | 0.5298 | 0.5351 | 0.5340 | |
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| No log | 3.3333 | 20 | 0.5071 | 0.3871 | 0.4996 | |
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| No log | 3.6667 | 22 | 0.4892 | 0.3871 | 0.4817 | |
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| No log | 4.0 | 24 | 0.4557 | 0.5051 | 0.4597 | |
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| No log | 4.3333 | 26 | 0.5421 | 0.5205 | 0.5533 | |
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| No log | 4.6667 | 28 | 0.5017 | 0.5263 | 0.5115 | |
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| No log | 5.0 | 30 | 0.4329 | 0.5365 | 0.4364 | |
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| No log | 5.3333 | 32 | 0.4203 | 0.4431 | 0.4190 | |
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| No log | 5.6667 | 34 | 0.4083 | 0.4848 | 0.4015 | |
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| No log | 6.0 | 36 | 0.4520 | 0.4167 | 0.4366 | |
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| No log | 6.3333 | 38 | 0.4291 | 0.4396 | 0.4158 | |
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| No log | 6.6667 | 40 | 0.4230 | 0.4324 | 0.4110 | |
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| No log | 7.0 | 42 | 0.4029 | 0.4848 | 0.3965 | |
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| No log | 7.3333 | 44 | 0.4095 | 0.4848 | 0.4043 | |
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| No log | 7.6667 | 46 | 0.4194 | 0.4149 | 0.4149 | |
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| No log | 8.0 | 48 | 0.4324 | 0.5051 | 0.4317 | |
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| No log | 8.3333 | 50 | 0.4591 | 0.5051 | 0.4628 | |
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| No log | 8.6667 | 52 | 0.4758 | 0.4652 | 0.4811 | |
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| No log | 9.0 | 54 | 0.4791 | 0.4652 | 0.4844 | |
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| No log | 9.3333 | 56 | 0.4781 | 0.4652 | 0.4831 | |
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| No log | 9.6667 | 58 | 0.4760 | 0.5051 | 0.4806 | |
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| No log | 10.0 | 60 | 0.4765 | 0.5051 | 0.4812 | |
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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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