readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: tiny-mlm-glue-mnli-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-mnli-from-scratch-custom-tokenizer-target-glue-qqp
  
  This model is a fine-tuned version of [muhtasham/tiny-mlm-glue-mnli-from-scratch-custom-tokenizer](https://huggingface.co/muhtasham/tiny-mlm-glue-mnli-from-scratch-custom-tokenizer) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5250
  - Accuracy: 0.7449
  - F1: 0.6058
  
  ## 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     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.6373        | 0.04  | 500  | 0.6162          | 0.6563   | 0.3793 |
  | 0.6053        | 0.09  | 1000 | 0.5908          | 0.6817   | 0.4690 |
  | 0.5843        | 0.13  | 1500 | 0.5700          | 0.7007   | 0.5850 |
  | 0.5672        | 0.18  | 2000 | 0.5554          | 0.7173   | 0.5632 |
  | 0.5562        | 0.22  | 2500 | 0.5462          | 0.7277   | 0.5585 |
  | 0.5484        | 0.26  | 3000 | 0.5382          | 0.7325   | 0.5848 |
  | 0.5411        | 0.31  | 3500 | 0.5327          | 0.7384   | 0.6064 |
  | 0.5388        | 0.35  | 4000 | 0.5335          | 0.7334   | 0.6310 |
  | 0.5409        | 0.4   | 4500 | 0.5267          | 0.7416   | 0.6232 |
  | 0.5322        | 0.44  | 5000 | 0.5250          | 0.7449   | 0.6058 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  