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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_task2_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_vocabulary_task2_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: 0.5710 |
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- Qwk: 0.0911 |
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- Mse: 0.5727 |
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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 | 5.7084 | -0.0071 | 5.7092 | |
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| No log | 0.6667 | 4 | 2.7119 | 0.0524 | 2.7198 | |
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| No log | 1.0 | 6 | 1.4034 | -0.0198 | 1.4046 | |
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| No log | 1.3333 | 8 | 0.6439 | 0.0396 | 0.6441 | |
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| No log | 1.6667 | 10 | 0.6138 | 0.0 | 0.6150 | |
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| No log | 2.0 | 12 | 0.6664 | 0.0 | 0.6682 | |
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| No log | 2.3333 | 14 | 0.6604 | -0.0925 | 0.6596 | |
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| No log | 2.6667 | 16 | 0.5976 | 0.0526 | 0.5979 | |
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| No log | 3.0 | 18 | 0.6250 | 0.1747 | 0.6254 | |
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| No log | 3.3333 | 20 | 0.6646 | 0.1021 | 0.6644 | |
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| No log | 3.6667 | 22 | 0.5974 | 0.2396 | 0.5967 | |
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| No log | 4.0 | 24 | 0.5442 | 0.0911 | 0.5440 | |
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| No log | 4.3333 | 26 | 0.5490 | 0.0289 | 0.5512 | |
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| No log | 4.6667 | 28 | 0.5728 | 0.0 | 0.5758 | |
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| No log | 5.0 | 30 | 0.5435 | 0.0 | 0.5463 | |
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| No log | 5.3333 | 32 | 0.4958 | 0.2794 | 0.4980 | |
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| No log | 5.6667 | 34 | 0.4795 | 0.2105 | 0.4813 | |
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| No log | 6.0 | 36 | 0.4887 | 0.2167 | 0.4894 | |
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| No log | 6.3333 | 38 | 0.4972 | 0.2222 | 0.4980 | |
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| No log | 6.6667 | 40 | 0.5094 | 0.2222 | 0.5094 | |
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| No log | 7.0 | 42 | 0.5328 | 0.1198 | 0.5321 | |
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| No log | 7.3333 | 44 | 0.5401 | 0.1064 | 0.5397 | |
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| No log | 7.6667 | 46 | 0.5403 | 0.1064 | 0.5409 | |
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| No log | 8.0 | 48 | 0.5495 | 0.0911 | 0.5517 | |
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| No log | 8.3333 | 50 | 0.5683 | 0.0735 | 0.5711 | |
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| No log | 8.6667 | 52 | 0.5763 | 0.0735 | 0.5791 | |
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| No log | 9.0 | 54 | 0.5754 | 0.0911 | 0.5779 | |
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| No log | 9.3333 | 56 | 0.5725 | 0.0911 | 0.5748 | |
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| No log | 9.6667 | 58 | 0.5717 | 0.0911 | 0.5736 | |
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| No log | 10.0 | 60 | 0.5710 | 0.0911 | 0.5727 | |
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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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