readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - spearmanr
  model-index:
  - name: tiny-mlm-glue-mrpc-target-glue-stsb
    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-mrpc-target-glue-stsb
  
  This model is a fine-tuned version of [muhtasham/tiny-mlm-glue-mrpc](https://huggingface.co/muhtasham/tiny-mlm-glue-mrpc) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9256
  - Pearson: 0.8144
  - Spearmanr: 0.8124
  
  ## 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
  - num_epochs: 200
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|
  | 2.9549        | 2.78  | 500  | 1.1776          | 0.7187  | 0.7620    |
  | 0.9497        | 5.56  | 1000 | 1.1286          | 0.7777  | 0.8045    |
  | 0.7413        | 8.33  | 1500 | 1.0286          | 0.8024  | 0.8197    |
  | 0.6158        | 11.11 | 2000 | 0.8676          | 0.8181  | 0.8232    |
  | 0.5192        | 13.89 | 2500 | 0.9099          | 0.8164  | 0.8193    |
  | 0.4693        | 16.67 | 3000 | 1.0002          | 0.8169  | 0.8212    |
  | 0.4144        | 19.44 | 3500 | 0.8905          | 0.8185  | 0.8185    |
  | 0.3768        | 22.22 | 4000 | 0.9210          | 0.8193  | 0.8191    |
  | 0.3443        | 25.0  | 4500 | 0.9723          | 0.8201  | 0.8206    |
  | 0.3212        | 27.78 | 5000 | 0.9919          | 0.8157  | 0.8162    |
  | 0.3032        | 30.56 | 5500 | 0.9692          | 0.8164  | 0.8162    |
  | 0.2797        | 33.33 | 6000 | 0.9256          | 0.8144  | 0.8124    |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  