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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_mechanics_task7_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_baseline_mechanics_task7_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: 0.3972 |
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- Qwk: 0.6491 |
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- Mse: 0.3972 |
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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 | 1.3247 | 0.0816 | 1.3247 | |
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| No log | 0.6667 | 4 | 0.6683 | 0.4335 | 0.6683 | |
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| No log | 1.0 | 6 | 0.5559 | 0.4980 | 0.5559 | |
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| No log | 1.3333 | 8 | 0.6243 | 0.4454 | 0.6243 | |
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| No log | 1.6667 | 10 | 0.4715 | 0.6195 | 0.4715 | |
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| No log | 2.0 | 12 | 0.5116 | 0.6491 | 0.5116 | |
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| No log | 2.3333 | 14 | 0.6116 | 0.5702 | 0.6116 | |
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| No log | 2.6667 | 16 | 0.6154 | 0.5631 | 0.6154 | |
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| No log | 3.0 | 18 | 0.6351 | 0.4762 | 0.6351 | |
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| No log | 3.3333 | 20 | 0.4519 | 0.5248 | 0.4519 | |
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| No log | 3.6667 | 22 | 0.2987 | 0.6600 | 0.2987 | |
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| No log | 4.0 | 24 | 0.2664 | 0.6715 | 0.2664 | |
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| No log | 4.3333 | 26 | 0.3049 | 0.6491 | 0.3049 | |
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| No log | 4.6667 | 28 | 0.5042 | 0.5601 | 0.5042 | |
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| No log | 5.0 | 30 | 0.7298 | 0.4401 | 0.7298 | |
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| No log | 5.3333 | 32 | 0.7112 | 0.4401 | 0.7112 | |
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| No log | 5.6667 | 34 | 0.4277 | 0.6780 | 0.4277 | |
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| No log | 6.0 | 36 | 0.2880 | 0.7239 | 0.2880 | |
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| No log | 6.3333 | 38 | 0.2886 | 0.7239 | 0.2886 | |
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| No log | 6.6667 | 40 | 0.3219 | 0.7239 | 0.3219 | |
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| No log | 7.0 | 42 | 0.4290 | 0.6329 | 0.4290 | |
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| No log | 7.3333 | 44 | 0.5828 | 0.5497 | 0.5828 | |
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| No log | 7.6667 | 46 | 0.6367 | 0.5129 | 0.6367 | |
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| No log | 8.0 | 48 | 0.5900 | 0.5497 | 0.5900 | |
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| No log | 8.3333 | 50 | 0.4796 | 0.5955 | 0.4796 | |
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| No log | 8.6667 | 52 | 0.4272 | 0.6491 | 0.4272 | |
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| No log | 9.0 | 54 | 0.4126 | 0.6491 | 0.4126 | |
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| No log | 9.3333 | 56 | 0.4004 | 0.6491 | 0.4004 | |
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| No log | 9.6667 | 58 | 0.3997 | 0.6491 | 0.3997 | |
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| No log | 10.0 | 60 | 0.3972 | 0.6491 | 0.3972 | |
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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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