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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_task1_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_task1_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: 0.2694 |
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- Qwk: 0.0109 |
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- Mse: 0.2694 |
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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: 64 |
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- eval_batch_size: 64 |
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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 | 0.1333 | 2 | 2.2712 | 0.0 | 2.2712 | |
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| No log | 0.2667 | 4 | 0.8815 | 0.0019 | 0.8815 | |
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| No log | 0.4 | 6 | 0.2576 | 0.0339 | 0.2576 | |
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| No log | 0.5333 | 8 | 0.2104 | 0.0276 | 0.2104 | |
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| No log | 0.6667 | 10 | 0.3374 | 0.0345 | 0.3374 | |
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| No log | 0.8 | 12 | 0.2690 | 0.0323 | 0.2690 | |
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| No log | 0.9333 | 14 | 0.1682 | 0.0249 | 0.1682 | |
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| No log | 1.0667 | 16 | 0.1503 | 0.0339 | 0.1503 | |
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| No log | 1.2 | 18 | 0.1672 | 0.0339 | 0.1672 | |
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| No log | 1.3333 | 20 | 0.2563 | 0.0263 | 0.2563 | |
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| No log | 1.4667 | 22 | 0.3596 | 0.0519 | 0.3596 | |
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| No log | 1.6 | 24 | 0.3144 | 0.0507 | 0.3144 | |
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| No log | 1.7333 | 26 | 0.1940 | 0.0263 | 0.1940 | |
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| No log | 1.8667 | 28 | 0.1460 | 0.0400 | 0.1460 | |
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| No log | 2.0 | 30 | 0.1369 | 0.0364 | 0.1369 | |
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| No log | 2.1333 | 32 | 0.1324 | 0.0372 | 0.1324 | |
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| No log | 2.2667 | 34 | 0.1415 | 0.0339 | 0.1415 | |
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| No log | 2.4 | 36 | 0.1809 | 0.0339 | 0.1809 | |
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| No log | 2.5333 | 38 | 0.2294 | 0.0339 | 0.2294 | |
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| No log | 2.6667 | 40 | 0.2654 | 0.0281 | 0.2654 | |
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| No log | 2.8 | 42 | 0.2940 | 0.0245 | 0.2940 | |
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| No log | 2.9333 | 44 | 0.2676 | 0.0245 | 0.2676 | |
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| No log | 3.0667 | 46 | 0.2359 | 0.0245 | 0.2359 | |
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| No log | 3.2 | 48 | 0.2040 | 0.0263 | 0.2040 | |
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| No log | 3.3333 | 50 | 0.1696 | 0.0300 | 0.1696 | |
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| No log | 3.4667 | 52 | 0.1616 | 0.0339 | 0.1616 | |
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| No log | 3.6 | 54 | 0.1702 | 0.0319 | 0.1702 | |
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| No log | 3.7333 | 56 | 0.2010 | 0.0281 | 0.2010 | |
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| No log | 3.8667 | 58 | 0.2570 | 0.0228 | 0.2570 | |
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| No log | 4.0 | 60 | 0.3107 | 0.0327 | 0.3107 | |
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| No log | 4.1333 | 62 | 0.3132 | 0.0327 | 0.3132 | |
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| No log | 4.2667 | 64 | 0.2646 | 0.0288 | 0.2646 | |
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| No log | 4.4 | 66 | 0.2086 | 0.0263 | 0.2086 | |
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| No log | 4.5333 | 68 | 0.1708 | 0.0300 | 0.1708 | |
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| No log | 4.6667 | 70 | 0.1646 | 0.0179 | 0.1646 | |
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| No log | 4.8 | 72 | 0.1786 | 0.0144 | 0.1786 | |
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| No log | 4.9333 | 74 | 0.2198 | 0.0281 | 0.2198 | |
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| No log | 5.0667 | 76 | 0.2585 | 0.0245 | 0.2585 | |
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| No log | 5.2 | 78 | 0.2513 | 0.0263 | 0.2513 | |
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| No log | 5.3333 | 80 | 0.2441 | 0.0263 | 0.2441 | |
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| No log | 5.4667 | 82 | 0.2186 | 0.0197 | 0.2186 | |
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| No log | 5.6 | 84 | 0.2061 | 0.0197 | 0.2061 | |
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| No log | 5.7333 | 86 | 0.2178 | 0.0197 | 0.2178 | |
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| No log | 5.8667 | 88 | 0.2322 | 0.0197 | 0.2322 | |
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| No log | 6.0 | 90 | 0.2425 | 0.0245 | 0.2425 | |
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| No log | 6.1333 | 92 | 0.2585 | 0.0245 | 0.2585 | |
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| No log | 6.2667 | 94 | 0.2369 | 0.0195 | 0.2369 | |
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| No log | 6.4 | 96 | 0.2110 | 0.0158 | 0.2110 | |
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| No log | 6.5333 | 98 | 0.2006 | 0.0158 | 0.2006 | |
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| No log | 6.6667 | 100 | 0.2175 | 0.0158 | 0.2175 | |
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| No log | 6.8 | 102 | 0.2464 | 0.0210 | 0.2464 | |
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| No log | 6.9333 | 104 | 0.2615 | 0.0225 | 0.2615 | |
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| No log | 7.0667 | 106 | 0.2784 | 0.0288 | 0.2784 | |
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| No log | 7.2 | 108 | 0.2991 | 0.0327 | 0.2991 | |
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| No log | 7.3333 | 110 | 0.2942 | 0.0327 | 0.2942 | |
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| No log | 7.4667 | 112 | 0.3083 | 0.0399 | 0.3083 | |
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| No log | 7.6 | 114 | 0.2910 | 0.0221 | 0.2910 | |
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| No log | 7.7333 | 116 | 0.2561 | 0.0093 | 0.2561 | |
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| No log | 7.8667 | 118 | 0.2246 | 0.0125 | 0.2246 | |
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| No log | 8.0 | 120 | 0.2152 | 0.0156 | 0.2152 | |
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| No log | 8.1333 | 122 | 0.2131 | 0.0156 | 0.2131 | |
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| No log | 8.2667 | 124 | 0.2238 | 0.0140 | 0.2238 | |
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| No log | 8.4 | 126 | 0.2341 | 0.0123 | 0.2341 | |
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| No log | 8.5333 | 128 | 0.2459 | 0.0123 | 0.2459 | |
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| No log | 8.6667 | 130 | 0.2510 | 0.0123 | 0.2510 | |
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| No log | 8.8 | 132 | 0.2702 | 0.0109 | 0.2702 | |
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| No log | 8.9333 | 134 | 0.2776 | 0.0093 | 0.2776 | |
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| No log | 9.0667 | 136 | 0.2862 | 0.0173 | 0.2862 | |
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| No log | 9.2 | 138 | 0.2916 | 0.0158 | 0.2916 | |
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| No log | 9.3333 | 140 | 0.2853 | 0.0158 | 0.2853 | |
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| No log | 9.4667 | 142 | 0.2781 | 0.0173 | 0.2781 | |
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| No log | 9.6 | 144 | 0.2737 | 0.0093 | 0.2737 | |
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| No log | 9.7333 | 146 | 0.2709 | 0.0109 | 0.2709 | |
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| No log | 9.8667 | 148 | 0.2693 | 0.0109 | 0.2693 | |
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| No log | 10.0 | 150 | 0.2694 | 0.0109 | 0.2694 | |
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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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