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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_organization_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_organization_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: 0.4509 |
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- Qwk: 0.6 |
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- Mse: 0.4509 |
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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 | 1.2538 | 0.1333 | 1.2538 | |
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| No log | 0.6667 | 4 | 0.6732 | 0.5116 | 0.6732 | |
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| No log | 1.0 | 6 | 1.0128 | 0.3810 | 1.0128 | |
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| No log | 1.3333 | 8 | 0.6424 | 0.5455 | 0.6424 | |
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| No log | 1.6667 | 10 | 0.6331 | 0.5455 | 0.6331 | |
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| No log | 2.0 | 12 | 0.6841 | 0.5455 | 0.6841 | |
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| No log | 2.3333 | 14 | 0.6488 | 0.5306 | 0.6488 | |
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| No log | 2.6667 | 16 | 0.7438 | 0.5185 | 0.7438 | |
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| No log | 3.0 | 18 | 1.0106 | 0.3636 | 1.0106 | |
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| No log | 3.3333 | 20 | 1.0009 | 0.3810 | 1.0009 | |
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| No log | 3.6667 | 22 | 0.6870 | 0.5098 | 0.6870 | |
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| No log | 4.0 | 24 | 0.5375 | 0.5106 | 0.5375 | |
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| No log | 4.3333 | 26 | 0.5197 | 0.55 | 0.5197 | |
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| No log | 4.6667 | 28 | 0.5082 | 0.5366 | 0.5082 | |
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| No log | 5.0 | 30 | 0.5130 | 0.5652 | 0.5130 | |
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| No log | 5.3333 | 32 | 0.5730 | 0.56 | 0.5730 | |
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| No log | 5.6667 | 34 | 0.5916 | 0.56 | 0.5916 | |
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| No log | 6.0 | 36 | 0.5065 | 0.5306 | 0.5065 | |
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| No log | 6.3333 | 38 | 0.4667 | 0.6 | 0.4667 | |
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| No log | 6.6667 | 40 | 0.4403 | 0.6 | 0.4403 | |
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| No log | 7.0 | 42 | 0.4374 | 0.6 | 0.4374 | |
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| No log | 7.3333 | 44 | 0.4427 | 0.6 | 0.4427 | |
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| No log | 7.6667 | 46 | 0.4590 | 0.6 | 0.4590 | |
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| No log | 8.0 | 48 | 0.4783 | 0.6275 | 0.4783 | |
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| No log | 8.3333 | 50 | 0.4751 | 0.6275 | 0.4751 | |
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| No log | 8.6667 | 52 | 0.4701 | 0.6275 | 0.4701 | |
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| No log | 9.0 | 54 | 0.4678 | 0.6275 | 0.4678 | |
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| No log | 9.3333 | 56 | 0.4574 | 0.6275 | 0.4574 | |
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| No log | 9.6667 | 58 | 0.4535 | 0.6 | 0.4535 | |
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| No log | 10.0 | 60 | 0.4509 | 0.6 | 0.4509 | |
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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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