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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_task6_fold6 |
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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_task6_fold6 |
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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: 0.4868 |
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- Qwk: 0.6478 |
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- Mse: 0.4856 |
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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 | 2.1344 | 0.0845 | 2.1260 | |
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| No log | 0.0615 | 4 | 1.0808 | 0.2961 | 1.0693 | |
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| No log | 0.0923 | 6 | 1.3454 | 0.2890 | 1.3254 | |
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| No log | 0.1231 | 8 | 0.6739 | 0.5314 | 0.6662 | |
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| No log | 0.1538 | 10 | 0.5779 | 0.6649 | 0.5736 | |
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| No log | 0.1846 | 12 | 0.5912 | 0.7569 | 0.5902 | |
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| No log | 0.2154 | 14 | 0.5775 | 0.7630 | 0.5772 | |
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| No log | 0.2462 | 16 | 0.5694 | 0.6622 | 0.5684 | |
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| No log | 0.2769 | 18 | 0.7642 | 0.5844 | 0.7634 | |
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| No log | 0.3077 | 20 | 1.2490 | 0.4005 | 1.2461 | |
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| No log | 0.3385 | 22 | 1.2661 | 0.3780 | 1.2624 | |
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| No log | 0.3692 | 24 | 0.8020 | 0.5334 | 0.8002 | |
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| No log | 0.4 | 26 | 0.6377 | 0.6083 | 0.6361 | |
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| No log | 0.4308 | 28 | 0.5794 | 0.6047 | 0.5774 | |
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| No log | 0.4615 | 30 | 0.5299 | 0.6342 | 0.5280 | |
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| No log | 0.4923 | 32 | 0.4877 | 0.6511 | 0.4861 | |
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| No log | 0.5231 | 34 | 0.4827 | 0.6483 | 0.4810 | |
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| No log | 0.5538 | 36 | 0.4477 | 0.7136 | 0.4467 | |
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| No log | 0.5846 | 38 | 0.4513 | 0.6644 | 0.4498 | |
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| No log | 0.6154 | 40 | 0.4864 | 0.6268 | 0.4842 | |
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| No log | 0.6462 | 42 | 0.5576 | 0.5786 | 0.5544 | |
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| No log | 0.6769 | 44 | 0.6809 | 0.4995 | 0.6764 | |
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| No log | 0.7077 | 46 | 0.7399 | 0.4954 | 0.7349 | |
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| No log | 0.7385 | 48 | 0.6881 | 0.4918 | 0.6838 | |
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| No log | 0.7692 | 50 | 0.6232 | 0.5309 | 0.6197 | |
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| No log | 0.8 | 52 | 0.5631 | 0.5592 | 0.5605 | |
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| No log | 0.8308 | 54 | 0.5054 | 0.6188 | 0.5036 | |
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| No log | 0.8615 | 56 | 0.4969 | 0.6158 | 0.4954 | |
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| No log | 0.8923 | 58 | 0.4962 | 0.6158 | 0.4947 | |
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| No log | 0.9231 | 60 | 0.4915 | 0.6233 | 0.4901 | |
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| No log | 0.9538 | 62 | 0.4898 | 0.6318 | 0.4885 | |
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| No log | 0.9846 | 64 | 0.4868 | 0.6478 | 0.4856 | |
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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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