readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: small-mlm-glue-qnli-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. -->
  
  # small-mlm-glue-qnli-target-glue-qqp
  
  This model is a fine-tuned version of [muhtasham/small-mlm-glue-qnli](https://huggingface.co/muhtasham/small-mlm-glue-qnli) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3296
  - Accuracy: 0.8511
  - F1: 0.8117
  
  ## 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     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.4762        | 0.04  | 500  | 0.4247          | 0.7897   | 0.7473 |
  | 0.4188        | 0.09  | 1000 | 0.3880          | 0.8126   | 0.7702 |
  | 0.4011        | 0.13  | 1500 | 0.3760          | 0.8194   | 0.7750 |
  | 0.387         | 0.18  | 2000 | 0.3779          | 0.8189   | 0.7866 |
  | 0.3802        | 0.22  | 2500 | 0.3642          | 0.8320   | 0.7958 |
  | 0.3606        | 0.26  | 3000 | 0.3526          | 0.8358   | 0.7972 |
  | 0.3604        | 0.31  | 3500 | 0.3337          | 0.8495   | 0.8010 |
  | 0.3538        | 0.35  | 4000 | 0.3341          | 0.8483   | 0.8102 |
  | 0.3582        | 0.4   | 4500 | 0.3293          | 0.8503   | 0.8106 |
  | 0.345         | 0.44  | 5000 | 0.3296          | 0.8511   | 0.8117 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  