readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: bert-small-juman-bpe
    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. -->
  
  # bert-small-juman-bpe
  
  This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
  It achieves the following results on the evaluation set:
  - Accuracy: 0.6317
  - Loss: 1.7829
  
  ## 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: 0.0001
  - train_batch_size: 256
  - eval_batch_size: 8
  - seed: 42
  - distributed_type: multi-GPU
  - num_devices: 3
  - total_train_batch_size: 768
  - total_eval_batch_size: 24
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.01
  - num_epochs: 14
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step   | Accuracy | Validation Loss |
  |:-------------:|:-----:|:------:|:--------:|:---------------:|
  | 2.3892        | 1.0   | 69472  | 0.5637   | 2.2498          |
  | 2.2219        | 2.0   | 138944 | 0.5873   | 2.0785          |
  | 2.1453        | 3.0   | 208416 | 0.5984   | 2.0019          |
  | 2.1           | 4.0   | 277888 | 0.6059   | 1.9531          |
  | 2.068         | 5.0   | 347360 | 0.6106   | 1.9169          |
  | 2.0405        | 6.0   | 416832 | 0.6146   | 1.8921          |
  | 2.0174        | 7.0   | 486304 | 0.6175   | 1.8711          |
  | 2.0002        | 8.0   | 555776 | 0.6205   | 1.8527          |
  | 1.9838        | 9.0   | 625248 | 0.6225   | 1.8381          |
  | 1.9691        | 10.0  | 694720 | 0.6248   | 1.8239          |
  | 1.9551        | 11.0  | 764192 | 0.6265   | 1.8125          |
  | 1.9406        | 12.0  | 833664 | 0.6288   | 1.8002          |
  | 1.9293        | 13.0  | 903136 | 0.6310   | 1.7871          |
  | 1.9247        | 14.0  | 972608 | 0.6317   | 1.7829          |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.12.0+cu116
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  