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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_cross_vocabulary_task4_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_cross_vocabulary_task4_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: 0.5474 |
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- Qwk: 0.4497 |
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- Mse: 0.5474 |
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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: 1 |
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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 | 0.0308 | 2 | 8.1440 | -0.0005 | 8.1440 | |
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| No log | 0.0615 | 4 | 4.7743 | 0.0021 | 4.7743 | |
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| No log | 0.0923 | 6 | 2.7118 | 0.0416 | 2.7118 | |
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| No log | 0.1231 | 8 | 1.7150 | 0.0799 | 1.7150 | |
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| No log | 0.1538 | 10 | 0.8541 | 0.1088 | 0.8541 | |
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| No log | 0.1846 | 12 | 0.8601 | 0.1094 | 0.8601 | |
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| No log | 0.2154 | 14 | 0.8470 | 0.1589 | 0.8470 | |
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| No log | 0.2462 | 16 | 1.0145 | 0.1789 | 1.0145 | |
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| No log | 0.2769 | 18 | 1.4913 | 0.1666 | 1.4913 | |
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| No log | 0.3077 | 20 | 1.4930 | 0.2073 | 1.4930 | |
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| No log | 0.3385 | 22 | 0.8055 | 0.3243 | 0.8055 | |
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| No log | 0.3692 | 24 | 0.5508 | 0.4354 | 0.5508 | |
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| No log | 0.4 | 26 | 0.6031 | 0.3790 | 0.6031 | |
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| No log | 0.4308 | 28 | 0.5860 | 0.4121 | 0.5860 | |
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| No log | 0.4615 | 30 | 0.6336 | 0.4190 | 0.6336 | |
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| No log | 0.4923 | 32 | 0.9905 | 0.3071 | 0.9905 | |
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| No log | 0.5231 | 34 | 1.0889 | 0.2932 | 1.0889 | |
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| No log | 0.5538 | 36 | 0.8745 | 0.3389 | 0.8745 | |
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| No log | 0.5846 | 38 | 0.7332 | 0.3681 | 0.7332 | |
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| No log | 0.6154 | 40 | 0.6486 | 0.3927 | 0.6486 | |
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| No log | 0.6462 | 42 | 0.6347 | 0.3914 | 0.6347 | |
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| No log | 0.6769 | 44 | 0.6439 | 0.3923 | 0.6439 | |
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| No log | 0.7077 | 46 | 0.6224 | 0.4042 | 0.6224 | |
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| No log | 0.7385 | 48 | 0.6224 | 0.4075 | 0.6224 | |
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| No log | 0.7692 | 50 | 0.5740 | 0.4350 | 0.5740 | |
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| No log | 0.8 | 52 | 0.5606 | 0.4443 | 0.5606 | |
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| No log | 0.8308 | 54 | 0.5580 | 0.4473 | 0.5580 | |
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| No log | 0.8615 | 56 | 0.5443 | 0.4451 | 0.5443 | |
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| No log | 0.8923 | 58 | 0.5430 | 0.4451 | 0.5430 | |
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| No log | 0.9231 | 60 | 0.5370 | 0.4575 | 0.5370 | |
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| No log | 0.9538 | 62 | 0.5412 | 0.4517 | 0.5412 | |
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| No log | 0.9846 | 64 | 0.5474 | 0.4497 | 0.5474 | |
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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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