readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: results
    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. -->
  
  # results
  
  This model is a fine-tuned version of [google/bert_uncased_L-4_H-512_A-8](https://huggingface.co/google/bert_uncased_L-4_H-512_A-8) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.6627
  
  ## 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: 5e-05
  - train_batch_size: 8
  - eval_batch_size: 64
  - seed: 42
  - gradient_accumulation_steps: 8
  - total_train_batch_size: 64
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: cosine
  - num_epochs: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss |
  |:-------------:|:-----:|:-----:|:---------------:|
  | No log        | 0.49  | 500   | 3.5536          |
  | 3.752         | 0.97  | 1000  | 3.0406          |
  | 3.752         | 1.46  | 1500  | 2.7601          |
  | 2.6844        | 1.94  | 2000  | 2.5655          |
  | 2.6844        | 2.43  | 2500  | 2.4174          |
  | 2.3487        | 2.91  | 3000  | 2.3163          |
  | 2.3487        | 3.4   | 3500  | 2.2146          |
  | 2.1554        | 3.89  | 4000  | 2.1560          |
  | 2.1554        | 4.37  | 4500  | 2.0935          |
  | 2.019         | 4.86  | 5000  | 2.0375          |
  | 2.019         | 5.34  | 5500  | 1.9942          |
  | 1.9254        | 5.83  | 6000  | 1.9530          |
  | 1.9254        | 6.32  | 6500  | 1.9215          |
  | 1.8506        | 6.8   | 7000  | 1.8908          |
  | 1.8506        | 7.29  | 7500  | 1.8693          |
  | 1.793         | 7.77  | 8000  | 1.8399          |
  | 1.793         | 8.26  | 8500  | 1.8191          |
  | 1.7425        | 8.75  | 9000  | 1.8016          |
  | 1.7425        | 9.23  | 9500  | 1.7760          |
  | 1.7093        | 9.72  | 10000 | 1.7668          |
  | 1.7093        | 10.2  | 10500 | 1.7474          |
  | 1.6754        | 10.69 | 11000 | 1.7365          |
  | 1.6754        | 11.18 | 11500 | 1.7229          |
  | 1.6501        | 11.66 | 12000 | 1.7145          |
  | 1.6501        | 12.15 | 12500 | 1.7029          |
  | 1.633         | 12.63 | 13000 | 1.6965          |
  | 1.633         | 13.12 | 13500 | 1.6878          |
  | 1.6153        | 13.61 | 14000 | 1.6810          |
  | 1.6153        | 14.09 | 14500 | 1.6775          |
  | 1.6043        | 14.58 | 15000 | 1.6720          |
  | 1.6043        | 15.06 | 15500 | 1.6719          |
  | 1.5942        | 15.55 | 16000 | 1.6602          |
  | 1.5942        | 16.03 | 16500 | 1.6643          |
  | 1.5869        | 16.52 | 17000 | 1.6632          |
  | 1.5869        | 17.01 | 17500 | 1.6551          |
  | 1.5834        | 17.49 | 18000 | 1.6557          |
  | 1.5834        | 17.98 | 18500 | 1.6561          |
  | 1.5755        | 18.46 | 19000 | 1.6620          |
  | 1.5755        | 18.95 | 19500 | 1.6524          |
  | 1.5823        | 19.44 | 20000 | 1.6536          |
  | 1.5823        | 19.92 | 20500 | 1.6627          |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  