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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_task2_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_organization_task2_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: 0.4740 |
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- Qwk: 0.5263 |
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- Mse: 0.4884 |
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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 | 2.7474 | 0.0719 | 2.8478 | |
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| No log | 0.6667 | 4 | 0.9337 | 0.1600 | 0.9879 | |
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| No log | 1.0 | 6 | 0.4534 | 0.0 | 0.4764 | |
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| No log | 1.3333 | 8 | 0.7904 | -0.0408 | 0.7830 | |
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| No log | 1.6667 | 10 | 0.7018 | 0.0769 | 0.6973 | |
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| No log | 2.0 | 12 | 0.5298 | 0.2258 | 0.5356 | |
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| No log | 2.3333 | 14 | 0.4547 | 0.0 | 0.4751 | |
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| No log | 2.6667 | 16 | 0.4579 | 0.0 | 0.4810 | |
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| No log | 3.0 | 18 | 0.4621 | 0.0 | 0.4849 | |
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| No log | 3.3333 | 20 | 0.5042 | 0.1563 | 0.5232 | |
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| No log | 3.6667 | 22 | 0.5058 | 0.1905 | 0.5230 | |
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| No log | 4.0 | 24 | 0.4808 | 0.2623 | 0.4947 | |
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| No log | 4.3333 | 26 | 0.4464 | 0.4828 | 0.4576 | |
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| No log | 4.6667 | 28 | 0.3793 | 0.2258 | 0.3943 | |
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| No log | 5.0 | 30 | 0.3971 | 0.2623 | 0.4100 | |
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| No log | 5.3333 | 32 | 0.5018 | 0.5263 | 0.5120 | |
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| No log | 5.6667 | 34 | 0.5357 | 0.3390 | 0.5481 | |
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| No log | 6.0 | 36 | 0.4854 | 0.3000 | 0.5002 | |
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| No log | 6.3333 | 38 | 0.4022 | 0.2623 | 0.4219 | |
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| No log | 6.6667 | 40 | 0.4018 | 0.2597 | 0.4313 | |
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| No log | 7.0 | 42 | 0.4157 | 0.2597 | 0.4485 | |
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| No log | 7.3333 | 44 | 0.3858 | 0.2895 | 0.4130 | |
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| No log | 7.6667 | 46 | 0.3839 | 0.3200 | 0.4045 | |
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| No log | 8.0 | 48 | 0.4237 | 0.5263 | 0.4396 | |
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| No log | 8.3333 | 50 | 0.4462 | 0.5263 | 0.4608 | |
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| No log | 8.6667 | 52 | 0.4536 | 0.5263 | 0.4681 | |
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| No log | 9.0 | 54 | 0.4620 | 0.5263 | 0.4764 | |
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| No log | 9.3333 | 56 | 0.4700 | 0.5263 | 0.4842 | |
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| No log | 9.6667 | 58 | 0.4698 | 0.5263 | 0.4842 | |
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| No log | 10.0 | 60 | 0.4740 | 0.5263 | 0.4884 | |
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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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