readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: tiny-mlm-glue-qnli-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-qnli-from-scratch-custom-tokenizer-target-glue-qqp
  
  This model is a fine-tuned version of [muhtasham/tiny-mlm-glue-qnli-from-scratch-custom-tokenizer](https://huggingface.co/muhtasham/tiny-mlm-glue-qnli-from-scratch-custom-tokenizer) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5253
  - Accuracy: 0.7422
  - F1: 0.6175
  
  ## 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     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.6417        | 0.04  | 500  | 0.6186          | 0.6422   | 0.3915 |
  | 0.6074        | 0.09  | 1000 | 0.5913          | 0.6758   | 0.5148 |
  | 0.5863        | 0.13  | 1500 | 0.5734          | 0.6951   | 0.5694 |
  | 0.5727        | 0.18  | 2000 | 0.5628          | 0.7098   | 0.5369 |
  | 0.5576        | 0.22  | 2500 | 0.5505          | 0.7215   | 0.5756 |
  | 0.5502        | 0.26  | 3000 | 0.5428          | 0.7282   | 0.5839 |
  | 0.545         | 0.31  | 3500 | 0.5368          | 0.7340   | 0.5996 |
  | 0.5368        | 0.35  | 4000 | 0.5328          | 0.7342   | 0.6250 |
  | 0.5385        | 0.4   | 4500 | 0.5300          | 0.7359   | 0.6323 |
  | 0.5316        | 0.44  | 5000 | 0.5253          | 0.7422   | 0.6175 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  