readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: small-mlm-glue-qqp-custom-tokenizer
    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-mlm-glue-qqp-custom-tokenizer
  
  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: 5.0065
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|
  | 6.3631        | 0.4   | 500   | 5.9145          |
  | 5.6422        | 0.8   | 1000  | 5.8224          |
  | 5.4368        | 1.2   | 1500  | 5.6172          |
  | 5.1539        | 1.6   | 2000  | 5.4872          |
  | 5.0641        | 2.0   | 2500  | 5.5369          |
  | 4.9495        | 2.4   | 3000  | 5.3466          |
  | 4.8947        | 2.8   | 3500  | 5.4592          |
  | 4.9081        | 3.2   | 4000  | 5.3328          |
  | 4.7214        | 3.6   | 4500  | 5.3746          |
  | 4.7341        | 4.0   | 5000  | 5.3417          |
  | 4.6482        | 4.4   | 5500  | 5.2731          |
  | 4.628         | 4.8   | 6000  | 5.2716          |
  | 4.5801        | 5.2   | 6500  | 5.1364          |
  | 4.4967        | 5.6   | 7000  | 5.2167          |
  | 4.4984        | 6.0   | 7500  | 5.2133          |
  | 4.4255        | 6.4   | 8000  | 5.1228          |
  | 4.4459        | 6.8   | 8500  | 5.1664          |
  | 4.3732        | 7.2   | 9000  | 5.0800          |
  | 4.2546        | 7.6   | 9500  | 5.0616          |
  | 4.351         | 8.0   | 10000 | 5.1500          |
  | 4.2365        | 8.4   | 10500 | 5.0903          |
  | 4.2224        | 8.8   | 11000 | 5.0041          |
  | 4.2549        | 9.2   | 11500 | 5.0711          |
  | 4.1108        | 9.6   | 12000 | 5.1525          |
  | 4.1366        | 10.0  | 12500 | 5.0065          |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  