readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: tiny-vanilla-target-glue-sst2
    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. -->
  
  # tiny-vanilla-target-glue-sst2
  
  This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4800
  - Accuracy: 0.8245
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.6144        | 0.24  | 500  | 0.5259          | 0.7477   |
  | 0.4695        | 0.48  | 1000 | 0.4724          | 0.7752   |
  | 0.4058        | 0.71  | 1500 | 0.4509          | 0.7878   |
  | 0.3815        | 0.95  | 2000 | 0.4536          | 0.7993   |
  | 0.3447        | 1.19  | 2500 | 0.4393          | 0.8073   |
  | 0.3226        | 1.43  | 3000 | 0.4462          | 0.8039   |
  | 0.3065        | 1.66  | 3500 | 0.4392          | 0.8119   |
  | 0.2972        | 1.9   | 4000 | 0.4412          | 0.8096   |
  | 0.2778        | 2.14  | 4500 | 0.4665          | 0.8154   |
  | 0.2599        | 2.38  | 5000 | 0.4395          | 0.8211   |
  | 0.2503        | 2.61  | 5500 | 0.4468          | 0.8245   |
  | 0.2586        | 2.85  | 6000 | 0.4443          | 0.8268   |
  | 0.24          | 3.09  | 6500 | 0.4625          | 0.8200   |
  | 0.2353        | 3.33  | 7000 | 0.4556          | 0.8268   |
  | 0.2207        | 3.56  | 7500 | 0.4507          | 0.8291   |
  | 0.2177        | 3.8   | 8000 | 0.4809          | 0.8280   |
  | 0.2156        | 4.04  | 8500 | 0.5157          | 0.8234   |
  | 0.2073        | 4.28  | 9000 | 0.4800          | 0.8245   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  