readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: small-vanilla-target-glue-qqp
    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-qqp
  
  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: 0.3259
  - Accuracy: 0.8536
  - F1: 0.8135
  
  ## 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 | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.4725        | 0.04  | 500  | 0.4206          | 0.7941   | 0.7492 |
  | 0.4177        | 0.09  | 1000 | 0.3860          | 0.8157   | 0.7712 |
  | 0.4009        | 0.13  | 1500 | 0.3750          | 0.8221   | 0.7756 |
  | 0.3815        | 0.18  | 2000 | 0.3781          | 0.8206   | 0.7858 |
  | 0.3768        | 0.22  | 2500 | 0.3495          | 0.8395   | 0.7975 |
  | 0.3592        | 0.26  | 3000 | 0.3496          | 0.8379   | 0.7993 |
  | 0.359         | 0.31  | 3500 | 0.3291          | 0.8514   | 0.8020 |
  | 0.3504        | 0.35  | 4000 | 0.3342          | 0.8469   | 0.8057 |
  | 0.3582        | 0.4   | 4500 | 0.3345          | 0.8482   | 0.8095 |
  | 0.3434        | 0.44  | 5000 | 0.3259          | 0.8536   | 0.8135 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  