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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_organization_task7_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_organization_task7_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: 1.0235 |
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- Qwk: 0.3186 |
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- Mse: 1.0235 |
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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 | 4.5492 | 0.0033 | 4.5492 | |
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| No log | 0.2667 | 4 | 2.3313 | 0.0265 | 2.3313 | |
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| No log | 0.4 | 6 | 0.9380 | 0.1593 | 0.9380 | |
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| No log | 0.5333 | 8 | 0.7299 | 0.3211 | 0.7299 | |
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| No log | 0.6667 | 10 | 1.0765 | 0.2403 | 1.0765 | |
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| No log | 0.8 | 12 | 0.9948 | 0.2992 | 0.9948 | |
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| No log | 0.9333 | 14 | 0.7246 | 0.3691 | 0.7246 | |
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| No log | 1.0667 | 16 | 0.8317 | 0.3374 | 0.8317 | |
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| No log | 1.2 | 18 | 1.1310 | 0.2565 | 1.1310 | |
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| No log | 1.3333 | 20 | 0.8172 | 0.3590 | 0.8172 | |
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| No log | 1.4667 | 22 | 0.6362 | 0.4637 | 0.6362 | |
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| No log | 1.6 | 24 | 0.7141 | 0.4179 | 0.7141 | |
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| No log | 1.7333 | 26 | 0.8099 | 0.3916 | 0.8099 | |
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| No log | 1.8667 | 28 | 0.8171 | 0.3801 | 0.8171 | |
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| No log | 2.0 | 30 | 0.6256 | 0.4325 | 0.6256 | |
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| No log | 2.1333 | 32 | 0.6044 | 0.4368 | 0.6044 | |
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| No log | 2.2667 | 34 | 0.6559 | 0.4218 | 0.6559 | |
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| No log | 2.4 | 36 | 0.6944 | 0.4358 | 0.6944 | |
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| No log | 2.5333 | 38 | 0.8347 | 0.3992 | 0.8347 | |
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| No log | 2.6667 | 40 | 0.7015 | 0.4476 | 0.7015 | |
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| No log | 2.8 | 42 | 0.5980 | 0.4984 | 0.5980 | |
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| No log | 2.9333 | 44 | 0.6999 | 0.4162 | 0.6999 | |
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| No log | 3.0667 | 46 | 0.9852 | 0.3253 | 0.9852 | |
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| No log | 3.2 | 48 | 0.8781 | 0.3521 | 0.8781 | |
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| No log | 3.3333 | 50 | 0.6081 | 0.4705 | 0.6081 | |
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| No log | 3.4667 | 52 | 0.5650 | 0.5161 | 0.5650 | |
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| No log | 3.6 | 54 | 0.6909 | 0.4496 | 0.6909 | |
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| No log | 3.7333 | 56 | 0.9750 | 0.3479 | 0.9750 | |
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| No log | 3.8667 | 58 | 1.0120 | 0.3345 | 1.0120 | |
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| No log | 4.0 | 60 | 0.7745 | 0.3864 | 0.7745 | |
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| No log | 4.1333 | 62 | 0.5602 | 0.4789 | 0.5602 | |
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| No log | 4.2667 | 64 | 0.5317 | 0.5191 | 0.5317 | |
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| No log | 4.4 | 66 | 0.6043 | 0.4530 | 0.6043 | |
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| No log | 4.5333 | 68 | 0.9138 | 0.3450 | 0.9138 | |
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| No log | 4.6667 | 70 | 1.0543 | 0.2899 | 1.0543 | |
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| No log | 4.8 | 72 | 0.9173 | 0.3364 | 0.9173 | |
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| No log | 4.9333 | 74 | 0.6723 | 0.4180 | 0.6723 | |
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| No log | 5.0667 | 76 | 0.6232 | 0.4325 | 0.6232 | |
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| No log | 5.2 | 78 | 0.7547 | 0.3914 | 0.7547 | |
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| No log | 5.3333 | 80 | 0.9923 | 0.3422 | 0.9923 | |
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| No log | 5.4667 | 82 | 1.1410 | 0.3118 | 1.1410 | |
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| No log | 5.6 | 84 | 0.9779 | 0.3534 | 0.9779 | |
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| No log | 5.7333 | 86 | 0.8238 | 0.4080 | 0.8238 | |
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| No log | 5.8667 | 88 | 0.8201 | 0.4073 | 0.8201 | |
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| No log | 6.0 | 90 | 0.9149 | 0.3516 | 0.9149 | |
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| No log | 6.1333 | 92 | 1.0529 | 0.3263 | 1.0529 | |
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| No log | 6.2667 | 94 | 1.0383 | 0.3165 | 1.0383 | |
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| No log | 6.4 | 96 | 0.9200 | 0.3612 | 0.9200 | |
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| No log | 6.5333 | 98 | 0.8061 | 0.3776 | 0.8061 | |
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| No log | 6.6667 | 100 | 0.8442 | 0.3648 | 0.8442 | |
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| No log | 6.8 | 102 | 0.8632 | 0.3618 | 0.8632 | |
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| No log | 6.9333 | 104 | 0.8772 | 0.3675 | 0.8772 | |
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| No log | 7.0667 | 106 | 0.9942 | 0.3310 | 0.9942 | |
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| No log | 7.2 | 108 | 1.0411 | 0.3115 | 1.0411 | |
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| No log | 7.3333 | 110 | 0.9094 | 0.3720 | 0.9094 | |
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| No log | 7.4667 | 112 | 0.8811 | 0.3764 | 0.8811 | |
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| No log | 7.6 | 114 | 0.9874 | 0.3393 | 0.9874 | |
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| No log | 7.7333 | 116 | 1.1141 | 0.2953 | 1.1141 | |
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| No log | 7.8667 | 118 | 1.1732 | 0.2682 | 1.1732 | |
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| No log | 8.0 | 120 | 1.2079 | 0.2587 | 1.2079 | |
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| No log | 8.1333 | 122 | 1.1465 | 0.2875 | 1.1465 | |
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| No log | 8.2667 | 124 | 1.0235 | 0.3252 | 1.0235 | |
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| No log | 8.4 | 126 | 0.9569 | 0.3373 | 0.9569 | |
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| No log | 8.5333 | 128 | 0.9933 | 0.3246 | 0.9933 | |
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| No log | 8.6667 | 130 | 1.0961 | 0.2757 | 1.0961 | |
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| No log | 8.8 | 132 | 1.2178 | 0.2280 | 1.2178 | |
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| No log | 8.9333 | 134 | 1.2733 | 0.2266 | 1.2733 | |
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| No log | 9.0667 | 136 | 1.3165 | 0.2226 | 1.3165 | |
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| No log | 9.2 | 138 | 1.2781 | 0.2220 | 1.2781 | |
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| No log | 9.3333 | 140 | 1.2042 | 0.2320 | 1.2042 | |
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| No log | 9.4667 | 142 | 1.1543 | 0.2486 | 1.1543 | |
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| No log | 9.6 | 144 | 1.0986 | 0.2779 | 1.0986 | |
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| No log | 9.7333 | 146 | 1.0621 | 0.2914 | 1.0621 | |
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| No log | 9.8667 | 148 | 1.0338 | 0.3043 | 1.0338 | |
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| No log | 10.0 | 150 | 1.0235 | 0.3186 | 1.0235 | |
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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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