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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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model-index: |
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- name: Improved-Arabert-twitter-sentiment-No-dropout |
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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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# Improved-Arabert-twitter-sentiment-No-dropout |
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This model is a fine-tuned version of [aubmindlab/bert-base-arabertv2](https://huggingface.co/aubmindlab/bert-base-arabertv2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5434 |
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- Accuracy: 0.9 |
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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: 1e-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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- 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: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.5764 | 0.55 | 50 | 0.4925 | 0.79 | |
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| 0.3357 | 1.1 | 100 | 0.3094 | 0.88 | |
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| 0.2183 | 1.65 | 150 | 0.2971 | 0.87 | |
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| 0.2042 | 2.2 | 200 | 0.3013 | 0.89 | |
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| 0.1258 | 2.75 | 250 | 0.3038 | 0.9 | |
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| 0.1359 | 3.3 | 300 | 0.3114 | 0.89 | |
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| 0.0893 | 3.85 | 350 | 0.3108 | 0.91 | |
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| 0.0816 | 4.4 | 400 | 0.3569 | 0.9 | |
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| 0.071 | 4.95 | 450 | 0.3574 | 0.9 | |
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| 0.1043 | 5.49 | 500 | 0.4332 | 0.89 | |
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| 0.0407 | 6.04 | 550 | 0.4232 | 0.9 | |
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| 0.0378 | 6.59 | 600 | 0.4273 | 0.91 | |
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| 0.0341 | 7.14 | 650 | 0.4671 | 0.91 | |
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| 0.0226 | 7.69 | 700 | 0.5174 | 0.9 | |
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| 0.0215 | 8.24 | 750 | 0.4786 | 0.89 | |
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| 0.0329 | 8.79 | 800 | 0.4853 | 0.9 | |
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| 0.021 | 9.34 | 850 | 0.5430 | 0.9 | |
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| 0.0219 | 9.89 | 900 | 0.5510 | 0.89 | |
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| 0.0154 | 10.44 | 950 | 0.5518 | 0.9 | |
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| 0.0119 | 10.99 | 1000 | 0.5473 | 0.9 | |
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| 0.0108 | 11.54 | 1050 | 0.5285 | 0.9 | |
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| 0.0138 | 12.09 | 1100 | 0.5239 | 0.91 | |
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| 0.0133 | 12.64 | 1150 | 0.5584 | 0.89 | |
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| 0.0121 | 13.19 | 1200 | 0.5334 | 0.9 | |
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| 0.0063 | 13.74 | 1250 | 0.5325 | 0.91 | |
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| 0.0061 | 14.29 | 1300 | 0.5429 | 0.9 | |
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| 0.0105 | 14.84 | 1350 | 0.5434 | 0.9 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.7 |
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- Tokenizers 0.14.1 |
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