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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_baseline_vocabulary_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_baseline_vocabulary_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: 0.4434 |
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- Qwk: 0.7306 |
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- Mse: 0.4409 |
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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: 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 | 0.3333 | 2 | 1.1716 | 0.2597 | 1.1767 | |
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| No log | 0.6667 | 4 | 0.7370 | 0.5706 | 0.7641 | |
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| No log | 1.0 | 6 | 0.7497 | 0.5562 | 0.7703 | |
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| No log | 1.3333 | 8 | 0.6581 | 0.5987 | 0.6708 | |
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| No log | 1.6667 | 10 | 0.6557 | 0.4 | 0.6660 | |
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| No log | 2.0 | 12 | 0.4981 | 0.7242 | 0.5095 | |
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| No log | 2.3333 | 14 | 0.5966 | 0.5490 | 0.6027 | |
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| No log | 2.6667 | 16 | 0.7334 | 0.5273 | 0.7340 | |
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| No log | 3.0 | 18 | 0.7026 | 0.5268 | 0.7001 | |
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| No log | 3.3333 | 20 | 0.5537 | 0.6360 | 0.5517 | |
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| No log | 3.6667 | 22 | 0.5745 | 0.6402 | 0.5704 | |
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| No log | 4.0 | 24 | 0.6711 | 0.5418 | 0.6622 | |
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| No log | 4.3333 | 26 | 0.6481 | 0.5418 | 0.6370 | |
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| No log | 4.6667 | 28 | 0.5399 | 0.6015 | 0.5315 | |
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| No log | 5.0 | 30 | 0.4583 | 0.6890 | 0.4538 | |
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| No log | 5.3333 | 32 | 0.4300 | 0.7379 | 0.4272 | |
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| No log | 5.6667 | 34 | 0.4490 | 0.6402 | 0.4450 | |
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| No log | 6.0 | 36 | 0.5299 | 0.6360 | 0.5222 | |
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| No log | 6.3333 | 38 | 0.5460 | 0.5268 | 0.5387 | |
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| No log | 6.6667 | 40 | 0.4926 | 0.6360 | 0.4893 | |
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| No log | 7.0 | 42 | 0.4501 | 0.6402 | 0.4494 | |
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| No log | 7.3333 | 44 | 0.4428 | 0.7379 | 0.4421 | |
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| No log | 7.6667 | 46 | 0.4707 | 0.6360 | 0.4684 | |
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| No log | 8.0 | 48 | 0.4833 | 0.6360 | 0.4804 | |
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| No log | 8.3333 | 50 | 0.5033 | 0.6360 | 0.4988 | |
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| No log | 8.6667 | 52 | 0.5001 | 0.6360 | 0.4953 | |
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| No log | 9.0 | 54 | 0.4748 | 0.6833 | 0.4711 | |
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| No log | 9.3333 | 56 | 0.4541 | 0.6833 | 0.4512 | |
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| No log | 9.6667 | 58 | 0.4462 | 0.6833 | 0.4437 | |
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| No log | 10.0 | 60 | 0.4434 | 0.7306 | 0.4409 | |
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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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