readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: bert-small-juman-unigram
    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-unigram
  
  This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.4490
  - Accuracy: 0.6911
  
  ## 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   | Validation Loss | Accuracy |
  |:-------------:|:-----:|:------:|:---------------:|:--------:|
  | 1.9849        | 1.0   | 69472  | 1.8385          | 0.6286   |
  | 1.8444        | 2.0   | 138944 | 1.6912          | 0.6513   |
  | 1.7767        | 3.0   | 208416 | 1.6322          | 0.6610   |
  | 1.7357        | 4.0   | 277888 | 1.5931          | 0.6676   |
  | 1.709         | 5.0   | 347360 | 1.5636          | 0.6719   |
  | 1.6874        | 6.0   | 416832 | 1.5405          | 0.6756   |
  | 1.6707        | 7.0   | 486304 | 1.5221          | 0.6786   |
  | 1.6511        | 8.0   | 555776 | 1.5061          | 0.6817   |
  | 1.636         | 9.0   | 625248 | 1.4933          | 0.6837   |
  | 1.6295        | 10.0  | 694720 | 1.4784          | 0.6860   |
  | 1.6157        | 11.0  | 764192 | 1.4673          | 0.6879   |
  | 1.6027        | 12.0  | 833664 | 1.4605          | 0.6896   |
  | 1.5942        | 13.0  | 903136 | 1.4535          | 0.6904   |
  | 1.5866        | 14.0  | 972608 | 1.4490          | 0.6911   |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.12.0+cu116
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  