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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- emotone_ar |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: bert-base-arabic-finetuned-emotion |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: emotone_ar |
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type: emotone_ar |
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config: default |
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split: train[:90%] |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7415506958250497 |
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- name: F1 |
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type: f1 |
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value: 0.7406006078114171 |
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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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# bert-base-arabic-finetuned-emotion |
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This model is a fine-tuned version of [asafaya/bert-base-arabic](https://huggingface.co/asafaya/bert-base-arabic) on the emotone_ar dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8965 |
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- Accuracy: 0.7416 |
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- F1: 0.7406 |
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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: 64 |
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- eval_batch_size: 64 |
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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: 6 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 1.3476 | 1.0 | 142 | 0.8911 | 0.7008 | 0.6812 | |
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| 0.8204 | 2.0 | 284 | 0.8175 | 0.7276 | 0.7212 | |
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| 0.6227 | 3.0 | 426 | 0.8392 | 0.7376 | 0.7302 | |
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| 0.4816 | 4.0 | 568 | 0.8531 | 0.7435 | 0.7404 | |
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| 0.378 | 5.0 | 710 | 0.8817 | 0.7396 | 0.7388 | |
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| 0.3134 | 6.0 | 852 | 0.8965 | 0.7416 | 0.7406 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.0+cu116 |
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- Datasets 2.8.0 |
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- Tokenizers 0.13.2 |
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