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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_relevance_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_cross_relevance_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: 0.2152 |
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- Qwk: 0.1252 |
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- Mse: 0.2152 |
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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 | 0.0351 | 2 | 1.7444 | 0.0064 | 1.7443 | |
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| No log | 0.0702 | 4 | 0.5072 | 0.0044 | 0.5075 | |
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| No log | 0.1053 | 6 | 0.3202 | 0.1573 | 0.3202 | |
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| No log | 0.1404 | 8 | 0.2932 | 0.1238 | 0.2931 | |
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| No log | 0.1754 | 10 | 0.2459 | 0.0491 | 0.2459 | |
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| No log | 0.2105 | 12 | 0.2721 | 0.0611 | 0.2721 | |
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| No log | 0.2456 | 14 | 0.3258 | 0.1020 | 0.3257 | |
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| No log | 0.2807 | 16 | 0.3460 | 0.1206 | 0.3459 | |
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| No log | 0.3158 | 18 | 0.2997 | 0.1063 | 0.2996 | |
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| No log | 0.3509 | 20 | 0.2574 | 0.1124 | 0.2574 | |
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| No log | 0.3860 | 22 | 0.2457 | 0.1501 | 0.2457 | |
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| No log | 0.4211 | 24 | 0.2347 | 0.1830 | 0.2348 | |
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| No log | 0.4561 | 26 | 0.2255 | 0.1739 | 0.2255 | |
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| No log | 0.4912 | 28 | 0.2268 | 0.1123 | 0.2267 | |
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| No log | 0.5263 | 30 | 0.2372 | 0.1054 | 0.2370 | |
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| No log | 0.5614 | 32 | 0.2505 | 0.1020 | 0.2503 | |
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| No log | 0.5965 | 34 | 0.2609 | 0.1020 | 0.2606 | |
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| No log | 0.6316 | 36 | 0.2711 | 0.0959 | 0.2709 | |
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| No log | 0.6667 | 38 | 0.2674 | 0.0679 | 0.2672 | |
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| No log | 0.7018 | 40 | 0.2605 | 0.0756 | 0.2602 | |
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| No log | 0.7368 | 42 | 0.2455 | 0.0756 | 0.2453 | |
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| No log | 0.7719 | 44 | 0.2290 | 0.0756 | 0.2289 | |
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| No log | 0.8070 | 46 | 0.2191 | 0.0791 | 0.2190 | |
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| No log | 0.8421 | 48 | 0.2160 | 0.0898 | 0.2159 | |
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| No log | 0.8772 | 50 | 0.2154 | 0.1042 | 0.2153 | |
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| No log | 0.9123 | 52 | 0.2153 | 0.1215 | 0.2152 | |
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| No log | 0.9474 | 54 | 0.2154 | 0.1252 | 0.2153 | |
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| No log | 0.9825 | 56 | 0.2152 | 0.1252 | 0.2152 | |
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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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