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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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- accuracy |
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model-index: |
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- name: sagemaker-bert-base-intent1018_2 |
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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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# sagemaker-bert-base-intent1018_2 |
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This model is a fine-tuned version of [asafaya/bert-base-arabic](https://huggingface.co/asafaya/bert-base-arabic) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5145 |
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- Accuracy: 0.9017 |
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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: 3e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 20 |
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- mixed_precision_training: Native AMP |
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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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| No log | 1.0 | 88 | 4.0951 | 0.0470 | |
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| No log | 2.0 | 176 | 3.7455 | 0.2158 | |
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| No log | 3.0 | 264 | 3.0505 | 0.4252 | |
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| No log | 4.0 | 352 | 2.0489 | 0.6303 | |
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| No log | 5.0 | 440 | 1.3342 | 0.7735 | |
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| 2.9556 | 6.0 | 528 | 0.9592 | 0.8162 | |
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| 2.9556 | 7.0 | 616 | 0.7623 | 0.8162 | |
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| 2.9556 | 8.0 | 704 | 0.6262 | 0.8547 | |
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| 2.9556 | 9.0 | 792 | 0.5145 | 0.9017 | |
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| 2.9556 | 10.0 | 880 | 0.5328 | 0.8846 | |
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| 2.9556 | 11.0 | 968 | 0.5137 | 0.8932 | |
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| 0.3206 | 12.0 | 1056 | 0.5190 | 0.8846 | |
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| 0.3206 | 13.0 | 1144 | 0.5158 | 0.8953 | |
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| 0.3206 | 14.0 | 1232 | 0.5053 | 0.8974 | |
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| 0.3206 | 15.0 | 1320 | 0.5140 | 0.8953 | |
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| 0.3206 | 16.0 | 1408 | 0.5108 | 0.8996 | |
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| 0.3206 | 17.0 | 1496 | 0.5282 | 0.8932 | |
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| 0.0381 | 18.0 | 1584 | 0.5278 | 0.8974 | |
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| 0.0381 | 19.0 | 1672 | 0.5224 | 0.8996 | |
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| 0.0381 | 20.0 | 1760 | 0.5226 | 0.8996 | |
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### Framework versions |
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- Transformers 4.12.3 |
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- Pytorch 1.9.1 |
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- Datasets 1.15.1 |
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- Tokenizers 0.10.3 |
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