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--- |
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base_model: aubmindlab/bert-base-arabertv2 |
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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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- recall |
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model-index: |
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- name: AraBert-finetuned-text-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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# AraBert-finetuned-text-classification |
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This model is a fine-tuned version of [aubmindlab/bert-base-arabertv2](https://huggingface.co/aubmindlab/bert-base-arabertv2) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1147 |
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- Macro F1: 0.9623 |
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- Accuracy: 0.9623 |
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- Recall: 0.9622 |
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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: 4e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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 | Accuracy | Validation Loss | Macro F1 | Recall | |
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|:-------------:|:-----:|:----:|:--------:|:---------------:|:--------:|:------:| |
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| No log | 0.99 | 56 | 0.9430 | 0.1530 | 0.9427 | 0.9425 | |
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| No log | 1.99 | 112 | 0.9579 | 0.1230 | 0.9577 | 0.9577 | |
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| No log | 3.0 | 169 | 0.9607 | 0.1287 | 0.9605 | 0.9608 | |
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| No log | 3.99 | 225 | 0.9618 | 0.1296 | 0.9616 | 0.9618 | |
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| No log | 5.0 | 282 | 0.9623 | 0.1147 | 0.9623 | 0.9622 | |
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| No log | 5.99 | 338 | 0.9612 | 0.1500 | 0.9611 | 0.9612 | |
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| No log | 7.0 | 395 | 0.9601 | 0.1953 | 0.9599 | 0.9602 | |
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| No log | 7.99 | 451 | 0.9640 | 0.1713 | 0.9639 | 0.9640 | |
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| 0.0526 | 9.0 | 508 | 0.9646 | 0.1748 | 0.9644 | 0.9645 | |
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| 0.0526 | 9.92 | 560 | 0.9646 | 0.1768 | 0.9644 | 0.9645 | |
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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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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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