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--- |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: AraBERT_token_classification_AraEval24_18_labels_augmented_fixed2 |
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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_token_classification_AraEval24_18_labels_augmented_fixed2 |
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This model is a fine-tuned version of [aubmindlab/bert-base-arabert](https://huggingface.co/aubmindlab/bert-base-arabert) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8169 |
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- Precision: 0.0952 |
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- Recall: 0.0280 |
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- F1: 0.0432 |
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- Accuracy: 0.8714 |
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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: 8 |
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- eval_batch_size: 8 |
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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 | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.684 | 1.0 | 3215 | 0.7004 | 0.0 | 0.0 | 0.0 | 0.8767 | |
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| 0.5935 | 2.0 | 6430 | 0.6946 | 0.0909 | 0.0005 | 0.0010 | 0.8765 | |
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| 0.5262 | 3.0 | 9645 | 0.7115 | 0.0952 | 0.0097 | 0.0176 | 0.8755 | |
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| 0.4585 | 4.0 | 12860 | 0.7140 | 0.0788 | 0.0204 | 0.0324 | 0.8718 | |
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| 0.4415 | 5.0 | 16075 | 0.7314 | 0.0982 | 0.0104 | 0.0188 | 0.8750 | |
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| 0.39 | 6.0 | 19290 | 0.7542 | 0.0942 | 0.0167 | 0.0284 | 0.8734 | |
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| 0.3668 | 7.0 | 22505 | 0.7570 | 0.0947 | 0.0230 | 0.0371 | 0.8721 | |
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| 0.3314 | 8.0 | 25720 | 0.8040 | 0.0887 | 0.0290 | 0.0437 | 0.8712 | |
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| 0.308 | 9.0 | 28935 | 0.7975 | 0.0977 | 0.0295 | 0.0454 | 0.8714 | |
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| 0.3007 | 10.0 | 32150 | 0.8169 | 0.0952 | 0.0280 | 0.0432 | 0.8714 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 1.12.1 |
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- Datasets 2.13.2 |
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- Tokenizers 0.13.3 |
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