readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: small-vanilla-target-glue-qnli
    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. -->
  
  # small-vanilla-target-glue-qnli
  
  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: 0.3458
  - Accuracy: 0.8583
  
  ## 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: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: constant
  - training_steps: 5000
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.488         | 0.15  | 500  | 0.3901          | 0.8316   |
  | 0.4449        | 0.31  | 1000 | 0.3826          | 0.8373   |
  | 0.4243        | 0.46  | 1500 | 0.3596          | 0.8448   |
  | 0.4133        | 0.61  | 2000 | 0.3663          | 0.8417   |
  | 0.4102        | 0.76  | 2500 | 0.3459          | 0.8499   |
  | 0.3924        | 0.92  | 3000 | 0.3286          | 0.8585   |
  | 0.3539        | 1.07  | 3500 | 0.3467          | 0.8532   |
  | 0.3202        | 1.22  | 4000 | 0.3478          | 0.8636   |
  | 0.3183        | 1.37  | 4500 | 0.3574          | 0.8514   |
  | 0.3215        | 1.53  | 5000 | 0.3458          | 0.8583   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  