readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: sagemaker-bert-base-intent1018_2
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # sagemaker-bert-base-intent1018_2
  
  This model is a fine-tuned version of [asafaya/bert-base-arabic](https://huggingface.co/asafaya/bert-base-arabic) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5145
  - Accuracy: 0.9017
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  More information needed
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 3e-05
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 20
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 1.0   | 88   | 4.0951          | 0.0470   |
  | No log        | 2.0   | 176  | 3.7455          | 0.2158   |
  | No log        | 3.0   | 264  | 3.0505          | 0.4252   |
  | No log        | 4.0   | 352  | 2.0489          | 0.6303   |
  | No log        | 5.0   | 440  | 1.3342          | 0.7735   |
  | 2.9556        | 6.0   | 528  | 0.9592          | 0.8162   |
  | 2.9556        | 7.0   | 616  | 0.7623          | 0.8162   |
  | 2.9556        | 8.0   | 704  | 0.6262          | 0.8547   |
  | 2.9556        | 9.0   | 792  | 0.5145          | 0.9017   |
  | 2.9556        | 10.0  | 880  | 0.5328          | 0.8846   |
  | 2.9556        | 11.0  | 968  | 0.5137          | 0.8932   |
  | 0.3206        | 12.0  | 1056 | 0.5190          | 0.8846   |
  | 0.3206        | 13.0  | 1144 | 0.5158          | 0.8953   |
  | 0.3206        | 14.0  | 1232 | 0.5053          | 0.8974   |
  | 0.3206        | 15.0  | 1320 | 0.5140          | 0.8953   |
  | 0.3206        | 16.0  | 1408 | 0.5108          | 0.8996   |
  | 0.3206        | 17.0  | 1496 | 0.5282          | 0.8932   |
  | 0.0381        | 18.0  | 1584 | 0.5278          | 0.8974   |
  | 0.0381        | 19.0  | 1672 | 0.5224          | 0.8996   |
  | 0.0381        | 20.0  | 1760 | 0.5226          | 0.8996   |
  
  
  ### Framework versions
  
  - Transformers 4.12.3
  - Pytorch 1.9.1
  - Datasets 1.15.1
  - Tokenizers 0.10.3
  