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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_task6_fold5 |
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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_task6_fold5 |
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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: 0.1873 |
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- Qwk: 0.3574 |
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- Mse: 0.1873 |
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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 | 0.0328 | 2 | 1.7597 | 0.0 | 1.7597 | |
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| No log | 0.0656 | 4 | 0.5562 | 0.1908 | 0.5562 | |
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| No log | 0.0984 | 6 | 0.1992 | 0.3305 | 0.1992 | |
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| No log | 0.1311 | 8 | 0.2333 | 0.4006 | 0.2333 | |
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| No log | 0.1639 | 10 | 0.2174 | 0.2998 | 0.2174 | |
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| No log | 0.1967 | 12 | 0.2464 | 0.2998 | 0.2464 | |
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| No log | 0.2295 | 14 | 0.2503 | 0.3279 | 0.2503 | |
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| No log | 0.2623 | 16 | 0.2466 | 0.3305 | 0.2466 | |
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| No log | 0.2951 | 18 | 0.2107 | 0.3279 | 0.2107 | |
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| No log | 0.3279 | 20 | 0.1965 | 0.3251 | 0.1965 | |
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| No log | 0.3607 | 22 | 0.1973 | 0.3292 | 0.1973 | |
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| No log | 0.3934 | 24 | 0.1930 | 0.3318 | 0.1930 | |
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| No log | 0.4262 | 26 | 0.1955 | 0.3379 | 0.1955 | |
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| No log | 0.4590 | 28 | 0.1901 | 0.3379 | 0.1901 | |
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| No log | 0.4918 | 30 | 0.1893 | 0.3343 | 0.1893 | |
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| No log | 0.5246 | 32 | 0.1861 | 0.3279 | 0.1861 | |
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| No log | 0.5574 | 34 | 0.1931 | 0.3453 | 0.1931 | |
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| No log | 0.5902 | 36 | 0.2045 | 0.5036 | 0.2045 | |
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| No log | 0.6230 | 38 | 0.2065 | 0.5858 | 0.2065 | |
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| No log | 0.6557 | 40 | 0.1891 | 0.4899 | 0.1891 | |
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| No log | 0.6885 | 42 | 0.1813 | 0.3696 | 0.1813 | |
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| No log | 0.7213 | 44 | 0.2125 | 0.3665 | 0.2125 | |
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| No log | 0.7541 | 46 | 0.2717 | 0.3526 | 0.2717 | |
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| No log | 0.7869 | 48 | 0.3306 | 0.3344 | 0.3306 | |
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| No log | 0.8197 | 50 | 0.3275 | 0.3475 | 0.3275 | |
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| No log | 0.8525 | 52 | 0.2862 | 0.3587 | 0.2862 | |
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| No log | 0.8852 | 54 | 0.2419 | 0.3643 | 0.2419 | |
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| No log | 0.9180 | 56 | 0.2102 | 0.3614 | 0.2102 | |
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| No log | 0.9508 | 58 | 0.1933 | 0.3590 | 0.1933 | |
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| No log | 0.9836 | 60 | 0.1873 | 0.3574 | 0.1873 | |
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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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