readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: small-vanilla-target-glue-mrpc
    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-mrpc
  
  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: 1.8756
  - Accuracy: 0.7696
  - F1: 0.8464
  
  ## 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
  - num_epochs: 200
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.3976        | 4.35  | 500  | 0.6055          | 0.7794   | 0.8469 |
  | 0.0776        | 8.7   | 1000 | 1.1540          | 0.7843   | 0.8585 |
  | 0.026         | 13.04 | 1500 | 1.3742          | 0.7892   | 0.8532 |
  | 0.0232        | 17.39 | 2000 | 1.5042          | 0.7819   | 0.8519 |
  | 0.011         | 21.74 | 2500 | 1.6290          | 0.7843   | 0.8467 |
  | 0.0132        | 26.09 | 3000 | 1.8756          | 0.7696   | 0.8464 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  