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Arabic_FineTuningAraBERT_AugV0_k3_task1_organization_fold1

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bert
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  1. README.md +194 -0
  2. config.json +32 -0
  3. model.safetensors +3 -0
  4. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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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: Arabic_FineTuningAraBERT_AugV0_k3_task1_organization_fold0
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+ results: []
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+ ---
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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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+
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+ # Arabic_FineTuningAraBERT_AugV0_k3_task1_organization_fold0
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+
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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: 0.8525
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+ - Qwk: 0.7063
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+ - Mse: 0.8525
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+ - Rmse: 0.9233
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 8
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+ - eval_batch_size: 8
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse |
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+ |:-------------:|:------:|:----:|:---------------:|:-------:|:------:|:------:|
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+ | No log | 0.0741 | 2 | 4.9259 | -0.0064 | 4.9259 | 2.2194 |
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+ | No log | 0.1481 | 4 | 2.6341 | 0.0968 | 2.6341 | 1.6230 |
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+ | No log | 0.2222 | 6 | 1.8715 | 0.1281 | 1.8715 | 1.3680 |
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+ | No log | 0.2963 | 8 | 1.7257 | 0.0056 | 1.7257 | 1.3136 |
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+ | No log | 0.3704 | 10 | 1.3136 | 0.0742 | 1.3136 | 1.1461 |
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+ | No log | 0.4444 | 12 | 1.3368 | 0.0 | 1.3368 | 1.1562 |
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+ | No log | 0.5185 | 14 | 1.3671 | 0.0 | 1.3671 | 1.1692 |
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+ | No log | 0.5926 | 16 | 1.3857 | 0.0758 | 1.3857 | 1.1772 |
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+ | No log | 0.6667 | 18 | 1.4480 | 0.3527 | 1.4480 | 1.2033 |
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+ | No log | 0.7407 | 20 | 1.4215 | 0.3527 | 1.4215 | 1.1923 |
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+ | No log | 0.8148 | 22 | 1.2583 | 0.2509 | 1.2583 | 1.1217 |
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+ | No log | 0.8889 | 24 | 1.2397 | 0.2667 | 1.2397 | 1.1134 |
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+ | No log | 0.9630 | 26 | 1.1883 | 0.3463 | 1.1883 | 1.0901 |
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+ | No log | 1.0370 | 28 | 1.1802 | 0.3718 | 1.1802 | 1.0864 |
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+ | No log | 1.1111 | 30 | 1.2183 | 0.3718 | 1.2183 | 1.1038 |
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+ | No log | 1.1852 | 32 | 1.1598 | 0.3718 | 1.1598 | 1.0770 |
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+ | No log | 1.2593 | 34 | 1.0985 | 0.3949 | 1.0985 | 1.0481 |
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+ | No log | 1.3333 | 36 | 1.1418 | 0.3893 | 1.1418 | 1.0685 |
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+ | No log | 1.4074 | 38 | 1.1392 | 0.4147 | 1.1392 | 1.0673 |
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+ | No log | 1.4815 | 40 | 1.2316 | 0.3845 | 1.2316 | 1.1098 |
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+ | No log | 1.5556 | 42 | 1.2784 | 0.4085 | 1.2784 | 1.1307 |
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+ | No log | 1.6296 | 44 | 1.1710 | 0.3860 | 1.1710 | 1.0821 |
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+ | No log | 1.7037 | 46 | 1.0806 | 0.4650 | 1.0806 | 1.0395 |
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+ | No log | 1.7778 | 48 | 1.1092 | 0.5084 | 1.1092 | 1.0532 |
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+ | No log | 1.8519 | 50 | 1.1840 | 0.3607 | 1.1840 | 1.0881 |
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+ | No log | 1.9259 | 52 | 1.1177 | 0.4134 | 1.1177 | 1.0572 |
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+ | No log | 2.0 | 54 | 0.9623 | 0.4856 | 0.9623 | 0.9810 |
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+ | No log | 2.0741 | 56 | 0.9207 | 0.4179 | 0.9207 | 0.9595 |
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+ | No log | 2.1481 | 58 | 1.0145 | 0.3893 | 1.0145 | 1.0072 |
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+ | No log | 2.2222 | 60 | 1.1236 | 0.3893 | 1.1236 | 1.0600 |
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+ | No log | 2.2963 | 62 | 1.1771 | 0.3893 | 1.1771 | 1.0849 |
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+ | No log | 2.3704 | 64 | 1.1101 | 0.3893 | 1.1101 | 1.0536 |
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+ | No log | 2.4444 | 66 | 0.9610 | 0.4 | 0.9610 | 0.9803 |
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+ | No log | 2.5185 | 68 | 0.9056 | 0.4 | 0.9056 | 0.9516 |
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+ | No log | 2.5926 | 70 | 0.9908 | 0.4 | 0.9908 | 0.9954 |
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+ | No log | 2.6667 | 72 | 1.0633 | 0.4047 | 1.0633 | 1.0312 |
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+ | No log | 2.7407 | 74 | 1.0943 | 0.4047 | 1.0943 | 1.0461 |
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+ | No log | 2.8148 | 76 | 1.0518 | 0.5288 | 1.0518 | 1.0256 |
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+ | No log | 2.8889 | 78 | 1.0347 | 0.4678 | 1.0347 | 1.0172 |
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+ | No log | 2.9630 | 80 | 0.9883 | 0.5288 | 0.9883 | 0.9941 |
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+ | No log | 3.0370 | 82 | 0.9285 | 0.5295 | 0.9285 | 0.9636 |
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+ | No log | 3.1111 | 84 | 1.0323 | 0.5733 | 1.0323 | 1.0160 |
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+ | No log | 3.1852 | 86 | 1.3281 | 0.4284 | 1.3281 | 1.1524 |
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+ | No log | 3.2593 | 88 | 1.4947 | 0.5696 | 1.4947 | 1.2226 |
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+ | No log | 3.3333 | 90 | 1.3968 | 0.5696 | 1.3968 | 1.1819 |
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+ | No log | 3.4074 | 92 | 1.1056 | 0.5494 | 1.1056 | 1.0515 |
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+ | No log | 3.4815 | 94 | 0.8487 | 0.6309 | 0.8487 | 0.9213 |
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+ | No log | 3.5556 | 96 | 0.8119 | 0.6309 | 0.8119 | 0.9011 |
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+ | No log | 3.6296 | 98 | 0.8671 | 0.6915 | 0.8671 | 0.9312 |
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+ | No log | 3.7037 | 100 | 0.9988 | 0.7206 | 0.9988 | 0.9994 |
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+ | No log | 3.7778 | 102 | 1.0625 | 0.6002 | 1.0625 | 1.0308 |
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+ | No log | 3.8519 | 104 | 1.0679 | 0.6002 | 1.0679 | 1.0334 |
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+ | No log | 3.9259 | 106 | 1.0555 | 0.6002 | 1.0555 | 1.0274 |
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+ | No log | 4.0 | 108 | 0.9803 | 0.4830 | 0.9803 | 0.9901 |
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+ | No log | 4.0741 | 110 | 0.9664 | 0.6002 | 0.9664 | 0.9830 |
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+ | No log | 4.1481 | 112 | 0.8558 | 0.6190 | 0.8558 | 0.9251 |
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+ | No log | 4.2222 | 114 | 0.8334 | 0.6994 | 0.8334 | 0.9129 |
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+ | No log | 4.2963 | 116 | 0.9191 | 0.6699 | 0.9191 | 0.9587 |
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+ | No log | 4.3704 | 118 | 1.1842 | 0.7322 | 1.1842 | 1.0882 |
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+ | No log | 4.4444 | 120 | 1.3107 | 0.7129 | 1.3107 | 1.1449 |
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+ | No log | 4.5185 | 122 | 1.1668 | 0.7322 | 1.1668 | 1.0802 |
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+ | No log | 4.5926 | 124 | 0.8619 | 0.7327 | 0.8619 | 0.9284 |
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+ | No log | 4.6667 | 126 | 0.7385 | 0.6521 | 0.7385 | 0.8594 |
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+ | No log | 4.7407 | 128 | 0.7660 | 0.6927 | 0.7660 | 0.8752 |
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+ | No log | 4.8148 | 130 | 0.9420 | 0.7162 | 0.9420 | 0.9705 |
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+ | No log | 4.8889 | 132 | 1.1254 | 0.6818 | 1.1254 | 1.0608 |
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+ | No log | 4.9630 | 134 | 1.1158 | 0.6818 | 1.1158 | 1.0563 |
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+ | No log | 5.0370 | 136 | 0.9750 | 0.6690 | 0.9750 | 0.9874 |
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+ | No log | 5.1111 | 138 | 0.8388 | 0.7439 | 0.8388 | 0.9158 |
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+ | No log | 5.1852 | 140 | 0.7333 | 0.7008 | 0.7333 | 0.8563 |
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+ | No log | 5.2593 | 142 | 0.7225 | 0.7008 | 0.7225 | 0.8500 |
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+ | No log | 5.3333 | 144 | 0.7934 | 0.7355 | 0.7934 | 0.8907 |
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+ | No log | 5.4074 | 146 | 0.8780 | 0.7823 | 0.8780 | 0.9370 |
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+ | No log | 5.4815 | 148 | 0.8834 | 0.7321 | 0.8834 | 0.9399 |
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+ | No log | 5.5556 | 150 | 0.8949 | 0.7321 | 0.8949 | 0.9460 |
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+ | No log | 5.6296 | 152 | 0.9098 | 0.7418 | 0.9098 | 0.9538 |
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+ | No log | 5.7037 | 154 | 0.9082 | 0.8142 | 0.9082 | 0.9530 |
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+ | No log | 5.7778 | 156 | 0.8676 | 0.7332 | 0.8676 | 0.9315 |
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+ | No log | 5.8519 | 158 | 0.8466 | 0.7612 | 0.8466 | 0.9201 |
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+ | No log | 5.9259 | 160 | 0.7979 | 0.7232 | 0.7979 | 0.8933 |
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+ | No log | 6.0 | 162 | 0.7660 | 0.7232 | 0.7660 | 0.8752 |
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+ | No log | 6.0741 | 164 | 0.8287 | 0.7321 | 0.8287 | 0.9103 |
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+ | No log | 6.1481 | 166 | 0.8279 | 0.7623 | 0.8279 | 0.9099 |
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+ | No log | 6.2222 | 168 | 0.8847 | 0.7623 | 0.8847 | 0.9406 |
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+ | No log | 6.2963 | 170 | 0.9216 | 0.7327 | 0.9216 | 0.9600 |
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+ | No log | 6.3704 | 172 | 0.9228 | 0.7322 | 0.9228 | 0.9606 |
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+ | No log | 6.4444 | 174 | 0.9261 | 0.7239 | 0.9261 | 0.9623 |
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+ | No log | 6.5185 | 176 | 0.9020 | 0.7239 | 0.9020 | 0.9497 |
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+ | No log | 6.5926 | 178 | 0.8292 | 0.6992 | 0.8292 | 0.9106 |
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+ | No log | 6.6667 | 180 | 0.8320 | 0.6992 | 0.8320 | 0.9121 |
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+ | No log | 6.7407 | 182 | 0.7987 | 0.6992 | 0.7987 | 0.8937 |
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+ | No log | 6.8148 | 184 | 0.7860 | 0.6992 | 0.7860 | 0.8866 |
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+ | No log | 6.8889 | 186 | 0.7506 | 0.7351 | 0.7506 | 0.8663 |
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+ | No log | 6.9630 | 188 | 0.7743 | 0.7351 | 0.7743 | 0.8799 |
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+ | No log | 7.0370 | 190 | 0.8212 | 0.7063 | 0.8212 | 0.9062 |
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+ | No log | 7.1111 | 192 | 0.9087 | 0.7139 | 0.9087 | 0.9533 |
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+ | No log | 7.1852 | 194 | 0.9039 | 0.7139 | 0.9039 | 0.9507 |
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+ | No log | 7.2593 | 196 | 0.8573 | 0.7063 | 0.8573 | 0.9259 |
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+ | No log | 7.3333 | 198 | 0.8690 | 0.6992 | 0.8690 | 0.9322 |
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+ | No log | 7.4074 | 200 | 0.9135 | 0.7063 | 0.9135 | 0.9558 |
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+ | No log | 7.4815 | 202 | 0.8735 | 0.6644 | 0.8735 | 0.9346 |
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+ | No log | 7.5556 | 204 | 0.8506 | 0.6644 | 0.8506 | 0.9223 |
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+ | No log | 7.6296 | 206 | 0.8681 | 0.6644 | 0.8681 | 0.9317 |
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+ | No log | 7.7037 | 208 | 0.8937 | 0.6702 | 0.8937 | 0.9453 |
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+ | No log | 7.7778 | 210 | 0.8845 | 0.6702 | 0.8845 | 0.9405 |
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+ | No log | 7.8519 | 212 | 0.8542 | 0.6702 | 0.8542 | 0.9242 |
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+ | No log | 7.9259 | 214 | 0.8578 | 0.6702 | 0.8578 | 0.9262 |
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+ | No log | 8.0 | 216 | 0.8515 | 0.6702 | 0.8515 | 0.9228 |
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+ | No log | 8.0741 | 218 | 0.8340 | 0.6992 | 0.8340 | 0.9133 |
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+ | No log | 8.1481 | 220 | 0.8157 | 0.6992 | 0.8157 | 0.9032 |
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+ | No log | 8.2222 | 222 | 0.8282 | 0.6992 | 0.8282 | 0.9101 |
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+ | No log | 8.2963 | 224 | 0.8311 | 0.6992 | 0.8311 | 0.9117 |
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+ | No log | 8.3704 | 226 | 0.8038 | 0.7063 | 0.8038 | 0.8966 |
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+ | No log | 8.4444 | 228 | 0.8074 | 0.6992 | 0.8074 | 0.8986 |
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+ | No log | 8.5185 | 230 | 0.8523 | 0.7063 | 0.8523 | 0.9232 |
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+ | No log | 8.5926 | 232 | 0.9302 | 0.6877 | 0.9302 | 0.9645 |
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+ | No log | 8.6667 | 234 | 1.0299 | 0.7129 | 1.0299 | 1.0148 |
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+ | No log | 8.7407 | 236 | 1.0633 | 0.7129 | 1.0633 | 1.0311 |
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+ | No log | 8.8148 | 238 | 1.0359 | 0.7129 | 1.0359 | 1.0178 |
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+ | No log | 8.8889 | 240 | 0.9717 | 0.7129 | 0.9717 | 0.9858 |
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+ | No log | 8.9630 | 242 | 0.9047 | 0.7063 | 0.9047 | 0.9512 |
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+ | No log | 9.0370 | 244 | 0.8793 | 0.7063 | 0.8793 | 0.9377 |
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+ | No log | 9.1111 | 246 | 0.8638 | 0.7063 | 0.8638 | 0.9294 |
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+ | No log | 9.1852 | 248 | 0.8613 | 0.7063 | 0.8613 | 0.9280 |
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+ | No log | 9.2593 | 250 | 0.8585 | 0.7063 | 0.8585 | 0.9265 |
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+ | No log | 9.3333 | 252 | 0.8446 | 0.7063 | 0.8446 | 0.9190 |
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+ | No log | 9.4074 | 254 | 0.8231 | 0.7063 | 0.8231 | 0.9072 |
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+ | No log | 9.4815 | 256 | 0.8169 | 0.7063 | 0.8169 | 0.9038 |
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+ | No log | 9.5556 | 258 | 0.8203 | 0.7063 | 0.8203 | 0.9057 |
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+ | No log | 9.6296 | 260 | 0.8253 | 0.7063 | 0.8253 | 0.9085 |
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+ | No log | 9.7037 | 262 | 0.8249 | 0.7063 | 0.8249 | 0.9083 |
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+ | No log | 9.7778 | 264 | 0.8318 | 0.7063 | 0.8318 | 0.9120 |
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+ | No log | 9.8519 | 266 | 0.8414 | 0.7063 | 0.8414 | 0.9173 |
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+ | No log | 9.9259 | 268 | 0.8492 | 0.7063 | 0.8492 | 0.9215 |
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+ | No log | 10.0 | 270 | 0.8525 | 0.7063 | 0.8525 | 0.9233 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.4.0+cu118
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+ - Datasets 2.21.0
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+ - Tokenizers 0.19.1
config.json ADDED
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+ {
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+ "_name_or_path": "aubmindlab/bert-base-arabertv02",
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+ "architectures": [
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+ "BertForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "classifier_dropout": null,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "LABEL_0"
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+ },
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "label2id": {
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+ "LABEL_0": 0
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 0,
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+ "position_embedding_type": "absolute",
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+ "problem_type": "regression",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.44.2",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 64000
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+ }
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training_args.bin ADDED
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