readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: tiny-mlm-glue-qqp-from-scratch-custom-tokenizer-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. -->
  
  # tiny-mlm-glue-qqp-from-scratch-custom-tokenizer-target-glue-qqp
  
  This model is a fine-tuned version of [muhtasham/tiny-mlm-glue-qqp-from-scratch-custom-tokenizer](https://huggingface.co/muhtasham/tiny-mlm-glue-qqp-from-scratch-custom-tokenizer) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5278
  - Accuracy: 0.7438
  - F1: 0.6220
  
  ## 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     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.6326        | 0.04  | 500  | 0.6031          | 0.6840   | 0.4888 |
  | 0.5912        | 0.09  | 1000 | 0.5873          | 0.6955   | 0.5272 |
  | 0.5854        | 0.13  | 1500 | 0.5739          | 0.7054   | 0.5911 |
  | 0.57          | 0.18  | 2000 | 0.5590          | 0.7193   | 0.5856 |
  | 0.5567        | 0.22  | 2500 | 0.5493          | 0.7283   | 0.5868 |
  | 0.5521        | 0.26  | 3000 | 0.5407          | 0.7335   | 0.5945 |
  | 0.5456        | 0.31  | 3500 | 0.5367          | 0.7354   | 0.6157 |
  | 0.5396        | 0.35  | 4000 | 0.5352          | 0.7360   | 0.6261 |
  | 0.5397        | 0.4   | 4500 | 0.5301          | 0.7388   | 0.6279 |
  | 0.5322        | 0.44  | 5000 | 0.5278          | 0.7438   | 0.6220 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  