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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_development_task7_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_development_task7_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: 0.3255 |
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- Qwk: 0.6 |
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- Mse: 0.3255 |
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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 | 1.1202 | 0.0777 | 1.1202 | |
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| No log | 0.6667 | 4 | 0.6041 | 0.4521 | 0.6041 | |
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| No log | 1.0 | 6 | 0.5933 | 0.4048 | 0.5933 | |
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| No log | 1.3333 | 8 | 0.6033 | 0.4186 | 0.6033 | |
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| No log | 1.6667 | 10 | 0.4045 | 0.5380 | 0.4045 | |
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| No log | 2.0 | 12 | 0.4962 | 0.5370 | 0.4962 | |
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| No log | 2.3333 | 14 | 0.4729 | 0.5380 | 0.4729 | |
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| No log | 2.6667 | 16 | 0.4672 | 0.4643 | 0.4672 | |
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| No log | 3.0 | 18 | 0.5466 | 0.4421 | 0.5466 | |
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| No log | 3.3333 | 20 | 0.6361 | 0.4508 | 0.6361 | |
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| No log | 3.6667 | 22 | 0.4635 | 0.4421 | 0.4635 | |
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| No log | 4.0 | 24 | 0.3643 | 0.6 | 0.3643 | |
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| No log | 4.3333 | 26 | 0.3664 | 0.6237 | 0.3664 | |
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| No log | 4.6667 | 28 | 0.3535 | 0.6 | 0.3535 | |
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| No log | 5.0 | 30 | 0.3681 | 0.5545 | 0.3681 | |
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| No log | 5.3333 | 32 | 0.3906 | 0.5327 | 0.3906 | |
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| No log | 5.6667 | 34 | 0.3676 | 0.5327 | 0.3676 | |
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| No log | 6.0 | 36 | 0.3373 | 0.6 | 0.3373 | |
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| No log | 6.3333 | 38 | 0.3425 | 0.6324 | 0.3425 | |
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| No log | 6.6667 | 40 | 0.3594 | 0.5960 | 0.3594 | |
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| No log | 7.0 | 42 | 0.3550 | 0.6 | 0.3550 | |
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| No log | 7.3333 | 44 | 0.3547 | 0.5874 | 0.3547 | |
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| No log | 7.6667 | 46 | 0.3761 | 0.5726 | 0.3761 | |
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| No log | 8.0 | 48 | 0.3915 | 0.5726 | 0.3915 | |
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| No log | 8.3333 | 50 | 0.3777 | 0.5726 | 0.3777 | |
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| No log | 8.6667 | 52 | 0.3558 | 0.5642 | 0.3558 | |
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| No log | 9.0 | 54 | 0.3383 | 0.5874 | 0.3383 | |
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| No log | 9.3333 | 56 | 0.3286 | 0.6 | 0.3286 | |
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| No log | 9.6667 | 58 | 0.3263 | 0.6 | 0.3263 | |
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| No log | 10.0 | 60 | 0.3255 | 0.6 | 0.3255 | |
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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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