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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_task1_fold3 |
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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_task1_fold3 |
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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: 0.6543 |
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- Qwk: 0.8547 |
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- Mse: 0.6543 |
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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 | 2.1991 | 0.1474 | 2.1991 | |
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| No log | 0.2667 | 4 | 1.6062 | 0.1520 | 1.6062 | |
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| No log | 0.4 | 6 | 1.5937 | 0.3436 | 1.5937 | |
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| No log | 0.5333 | 8 | 1.1613 | 0.6120 | 1.1613 | |
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| No log | 0.6667 | 10 | 1.0503 | 0.7478 | 1.0503 | |
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| No log | 0.8 | 12 | 0.7718 | 0.7837 | 0.7718 | |
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| No log | 0.9333 | 14 | 0.6578 | 0.7874 | 0.6578 | |
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| No log | 1.0667 | 16 | 0.6200 | 0.7876 | 0.6200 | |
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| No log | 1.2 | 18 | 0.6610 | 0.8102 | 0.6610 | |
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| No log | 1.3333 | 20 | 0.6508 | 0.8233 | 0.6508 | |
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| No log | 1.4667 | 22 | 0.6181 | 0.8360 | 0.6181 | |
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| No log | 1.6 | 24 | 0.6494 | 0.8333 | 0.6494 | |
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| No log | 1.7333 | 26 | 0.5220 | 0.7872 | 0.5220 | |
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| No log | 1.8667 | 28 | 0.5440 | 0.8098 | 0.5440 | |
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| No log | 2.0 | 30 | 0.6917 | 0.8299 | 0.6917 | |
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| No log | 2.1333 | 32 | 0.7100 | 0.8241 | 0.7100 | |
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| No log | 2.2667 | 34 | 0.6018 | 0.8256 | 0.6018 | |
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| No log | 2.4 | 36 | 0.5920 | 0.8362 | 0.5920 | |
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| No log | 2.5333 | 38 | 0.5900 | 0.8254 | 0.5900 | |
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| No log | 2.6667 | 40 | 0.5183 | 0.8071 | 0.5183 | |
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| No log | 2.8 | 42 | 0.5565 | 0.8214 | 0.5565 | |
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| No log | 2.9333 | 44 | 0.5828 | 0.8308 | 0.5828 | |
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| No log | 3.0667 | 46 | 0.6086 | 0.8345 | 0.6086 | |
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| No log | 3.2 | 48 | 0.9512 | 0.8040 | 0.9512 | |
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| No log | 3.3333 | 50 | 1.0514 | 0.7892 | 1.0514 | |
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| No log | 3.4667 | 52 | 0.7574 | 0.8307 | 0.7574 | |
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| No log | 3.6 | 54 | 0.5438 | 0.8157 | 0.5438 | |
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| No log | 3.7333 | 56 | 0.5688 | 0.8295 | 0.5688 | |
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| No log | 3.8667 | 58 | 0.7090 | 0.8272 | 0.7090 | |
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| No log | 4.0 | 60 | 0.6153 | 0.8315 | 0.6153 | |
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| No log | 4.1333 | 62 | 0.5938 | 0.8311 | 0.5938 | |
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| No log | 4.2667 | 64 | 0.5535 | 0.8284 | 0.5535 | |
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| No log | 4.4 | 66 | 0.7113 | 0.8397 | 0.7113 | |
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| No log | 4.5333 | 68 | 0.7956 | 0.8396 | 0.7956 | |
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| No log | 4.6667 | 70 | 0.6577 | 0.8415 | 0.6577 | |
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| No log | 4.8 | 72 | 0.5410 | 0.8175 | 0.5410 | |
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| No log | 4.9333 | 74 | 0.5447 | 0.8164 | 0.5447 | |
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| No log | 5.0667 | 76 | 0.6400 | 0.8362 | 0.6400 | |
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| No log | 5.2 | 78 | 0.6465 | 0.8350 | 0.6465 | |
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| No log | 5.3333 | 80 | 0.5521 | 0.8190 | 0.5521 | |
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| No log | 5.4667 | 82 | 0.5413 | 0.8159 | 0.5413 | |
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| No log | 5.6 | 84 | 0.5904 | 0.8356 | 0.5904 | |
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| No log | 5.7333 | 86 | 0.6050 | 0.8329 | 0.6050 | |
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| No log | 5.8667 | 88 | 0.5617 | 0.8344 | 0.5617 | |
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| No log | 6.0 | 90 | 0.5078 | 0.8086 | 0.5078 | |
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| No log | 6.1333 | 92 | 0.5744 | 0.8431 | 0.5744 | |
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| No log | 6.2667 | 94 | 0.8177 | 0.8508 | 0.8177 | |
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| No log | 6.4 | 96 | 0.9516 | 0.8372 | 0.9516 | |
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| No log | 6.5333 | 98 | 0.8522 | 0.8514 | 0.8522 | |
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| No log | 6.6667 | 100 | 0.6484 | 0.8513 | 0.6484 | |
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| No log | 6.8 | 102 | 0.5556 | 0.8426 | 0.5556 | |
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| No log | 6.9333 | 104 | 0.5410 | 0.8334 | 0.5410 | |
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| No log | 7.0667 | 106 | 0.6003 | 0.8457 | 0.6003 | |
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| No log | 7.2 | 108 | 0.6955 | 0.8578 | 0.6955 | |
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| No log | 7.3333 | 110 | 0.6870 | 0.8586 | 0.6870 | |
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| No log | 7.4667 | 112 | 0.6444 | 0.8510 | 0.6444 | |
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| No log | 7.6 | 114 | 0.5518 | 0.8355 | 0.5518 | |
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| No log | 7.7333 | 116 | 0.5347 | 0.8285 | 0.5347 | |
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| No log | 7.8667 | 118 | 0.5790 | 0.8402 | 0.5790 | |
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| No log | 8.0 | 120 | 0.6668 | 0.8499 | 0.6668 | |
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| No log | 8.1333 | 122 | 0.6878 | 0.8492 | 0.6878 | |
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| No log | 8.2667 | 124 | 0.6406 | 0.8545 | 0.6406 | |
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| No log | 8.4 | 126 | 0.6005 | 0.8510 | 0.6005 | |
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| No log | 8.5333 | 128 | 0.6017 | 0.8494 | 0.6017 | |
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| No log | 8.6667 | 130 | 0.5940 | 0.8481 | 0.5940 | |
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| No log | 8.8 | 132 | 0.5792 | 0.8445 | 0.5792 | |
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| No log | 8.9333 | 134 | 0.5857 | 0.8481 | 0.5857 | |
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| No log | 9.0667 | 136 | 0.6217 | 0.8492 | 0.6217 | |
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| No log | 9.2 | 138 | 0.6735 | 0.8562 | 0.6735 | |
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| No log | 9.3333 | 140 | 0.7067 | 0.8519 | 0.7067 | |
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| No log | 9.4667 | 142 | 0.7028 | 0.8584 | 0.7028 | |
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| No log | 9.6 | 144 | 0.7006 | 0.8584 | 0.7006 | |
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| No log | 9.7333 | 146 | 0.6820 | 0.8583 | 0.6820 | |
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| No log | 9.8667 | 148 | 0.6634 | 0.8629 | 0.6634 | |
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| No log | 10.0 | 150 | 0.6543 | 0.8547 | 0.6543 | |
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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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