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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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metrics: |
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- accuracy |
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model-index: |
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- name: ar-poem-classification |
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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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# ar-poem-classification |
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This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1427 |
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- Macro F1: 0.6954 |
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- Accuracy: 0.6944 |
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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: 128 |
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- seed: 25 |
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- gradient_accumulation_steps: 5 |
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- total_train_batch_size: 80 |
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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: 12 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:| |
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| No log | 1.0 | 250 | 1.0896 | 0.5319 | 0.5334 | |
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| 1.114 | 2.0 | 500 | 0.9989 | 0.5864 | 0.5826 | |
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| 1.114 | 3.0 | 750 | 0.9993 | 0.5942 | 0.5976 | |
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| 0.8219 | 4.0 | 1000 | 0.9949 | 0.6042 | 0.609 | |
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| 0.8219 | 5.0 | 1250 | 0.9813 | 0.6337 | 0.6366 | |
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| 0.563 | 6.0 | 1500 | 0.9666 | 0.6657 | 0.6654 | |
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| 0.563 | 7.0 | 1750 | 1.0253 | 0.6686 | 0.6668 | |
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| 0.3763 | 8.0 | 2000 | 1.0150 | 0.6951 | 0.6936 | |
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| 0.3763 | 9.0 | 2250 | 1.0619 | 0.6872 | 0.6872 | |
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| 0.2525 | 10.0 | 2500 | 1.1035 | 0.6929 | 0.6922 | |
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| 0.2525 | 11.0 | 2750 | 1.1352 | 0.6952 | 0.6944 | |
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| 0.184 | 12.0 | 3000 | 1.1427 | 0.6954 | 0.6944 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.1.0+cu121 |
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- Tokenizers 0.15.2 |
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