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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_task1_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_task1_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: 0.7080 |
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- Qwk: 0.6596 |
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- Mse: 0.7206 |
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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 | 4.7375 | -0.0187 | 4.6528 | |
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| No log | 0.6667 | 4 | 2.9523 | 0.0354 | 2.8976 | |
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| No log | 1.0 | 6 | 1.9933 | 0.0369 | 1.9520 | |
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| No log | 1.3333 | 8 | 1.4358 | 0.1414 | 1.4243 | |
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| No log | 1.6667 | 10 | 1.3507 | 0.0742 | 1.3574 | |
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| No log | 2.0 | 12 | 1.2869 | 0.3309 | 1.2992 | |
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| No log | 2.3333 | 14 | 1.3060 | 0.4324 | 1.3235 | |
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| No log | 2.6667 | 16 | 1.2124 | 0.4085 | 1.2278 | |
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| No log | 3.0 | 18 | 1.0567 | 0.4854 | 1.0647 | |
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| No log | 3.3333 | 20 | 0.9500 | 0.4639 | 0.9565 | |
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| No log | 3.6667 | 22 | 0.8719 | 0.5769 | 0.8846 | |
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| No log | 4.0 | 24 | 0.7991 | 0.5769 | 0.8115 | |
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| No log | 4.3333 | 26 | 0.7537 | 0.5769 | 0.7666 | |
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| No log | 4.6667 | 28 | 0.7147 | 0.5514 | 0.7274 | |
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| No log | 5.0 | 30 | 0.6387 | 0.5811 | 0.6471 | |
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| No log | 5.3333 | 32 | 0.6221 | 0.5748 | 0.6286 | |
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| No log | 5.6667 | 34 | 0.6363 | 0.5811 | 0.6453 | |
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| No log | 6.0 | 36 | 0.6849 | 0.5811 | 0.6955 | |
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| No log | 6.3333 | 38 | 0.6868 | 0.5811 | 0.6971 | |
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| No log | 6.6667 | 40 | 0.6843 | 0.5435 | 0.6932 | |
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| No log | 7.0 | 42 | 0.7048 | 0.5081 | 0.7131 | |
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| No log | 7.3333 | 44 | 0.7116 | 0.5804 | 0.7201 | |
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| No log | 7.6667 | 46 | 0.7162 | 0.5779 | 0.7250 | |
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| No log | 8.0 | 48 | 0.7262 | 0.5779 | 0.7360 | |
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| No log | 8.3333 | 50 | 0.7157 | 0.5779 | 0.7258 | |
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| No log | 8.6667 | 52 | 0.7189 | 0.5779 | 0.7301 | |
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| No log | 9.0 | 54 | 0.7090 | 0.6547 | 0.7206 | |
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| No log | 9.3333 | 56 | 0.7059 | 0.6547 | 0.7179 | |
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| No log | 9.6667 | 58 | 0.7067 | 0.6547 | 0.7191 | |
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| No log | 10.0 | 60 | 0.7080 | 0.6596 | 0.7206 | |
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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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