readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: bert-small-ipadic_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-ipadic_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:
  - Loss: 1.6777
  - Accuracy: 0.6519
  
  ## 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 |
  |:-------------:|:-----:|:------:|:---------------:|:--------:|
  | 2.2548        | 1.0   | 69473  | 2.1163          | 0.5882   |
  | 2.0904        | 2.0   | 138946 | 1.9562          | 0.6101   |
  | 2.0203        | 3.0   | 208419 | 1.8848          | 0.6208   |
  | 1.978         | 4.0   | 277892 | 1.8408          | 0.6272   |
  | 1.937         | 5.0   | 347365 | 1.8080          | 0.6320   |
  | 1.9152        | 6.0   | 416838 | 1.7818          | 0.6361   |
  | 1.8982        | 7.0   | 486311 | 1.7575          | 0.6395   |
  | 1.8808        | 8.0   | 555784 | 1.7413          | 0.6421   |
  | 1.8684        | 9.0   | 625257 | 1.7282          | 0.6440   |
  | 1.8517        | 10.0  | 694730 | 1.7140          | 0.6464   |
  | 1.8353        | 11.0  | 764203 | 1.7022          | 0.6481   |
  | 1.8245        | 12.0  | 833676 | 1.6877          | 0.6504   |
  | 1.8191        | 13.0  | 903149 | 1.6829          | 0.6515   |
  | 1.8122        | 14.0  | 972622 | 1.6777          | 0.6519   |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.12.0+cu116
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  