readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - matthews_correlation
  model-index:
  - name: paraphrase-MiniLM-L12-v2-CoLA
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: GLUE COLA
        type: glue
        config: cola
        split: validation
        args: cola
      metrics:
      - name: Matthews Correlation
        type: matthews_correlation
        value: 0.5057060886900621
  
  widget:
    - text: 'The cat sat on the mat.'
      example_title: Correct grammatical sentence
    - text: 'Me and my friend going to the store.'
      example_title: Incorrect subject-verb agreement
    - text: 'I ain''t got no money.'
      example_title: Incorrect verb conjugation and double negative
    - text: 'She don''t like pizza no more.'
      example_title: Incorrect verb conjugation and double negative
    - text: 'They is arriving tomorrow.'
      example_title: Incorrect verb conjugation
  ---
  
  <!-- 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. -->
  
  # paraphrase-MiniLM-L12-v2-CoLA
  
  This model is a fine-tuned version of [sentence-transformers/paraphrase-MiniLM-L12-v2](https://huggingface.co/sentence-transformers/paraphrase-MiniLM-L12-v2) on the GLUE COLA dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4636
  - Matthews Correlation: 0.5057
  
  ## 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: 8e-05
  - train_batch_size: 64
  - eval_batch_size: 16
  - seed: 30198
  - distributed_type: multi-GPU
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 128
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: cosine
  - lr_scheduler_warmup_ratio: 0.03
  - num_epochs: 16.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
  |:-------------:|:-----:|:----:|:---------------:|:--------------------:|
  | 0.5747        | 1.0   | 67   | 0.5394          | 0.3455               |
  | 0.5025        | 2.0   | 134  | 0.4999          | 0.4270               |
  | 0.3698        | 3.0   | 201  | 0.4636          | 0.5057               |
  | 0.2969        | 4.0   | 268  | 0.5309          | 0.4751               |
  | 0.2275        | 5.0   | 335  | 0.6238          | 0.4775               |
  | 0.1859        | 6.0   | 402  | 0.6315          | 0.4867               |
  | 0.1517        | 7.0   | 469  | 0.7783          | 0.4695               |
  | 0.1016        | 8.0   | 536  | 0.6762          | 0.4901               |
  | 0.1017        | 9.0   | 603  | 0.7412          | 0.5046               |
  | 0.0898        | 10.0  | 670  | 0.7719          | 0.4877               |
  | 0.0527        | 11.0  | 737  | 0.8627          | 0.4955               |
  | 0.0582        | 12.0  | 804  | 0.8986          | 0.4738               |
  | 0.074         | 13.0  | 871  | 0.9469          | 0.4942               |
  | 0.0508        | 14.0  | 938  | 0.9436          | 0.4918               |
  | 0.024         | 15.0  | 1005 | 0.9391          | 0.4919               |
  | 0.0458        | 16.0  | 1072 | 0.9375          | 0.4946               |
  
  
  ### Framework versions
  
  - Transformers 4.27.0.dev0
  - Pytorch 1.13.1+cu117
  - Datasets 2.8.0
  - Tokenizers 0.13.1
  