readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - spearmanr
  model-index:
  - name: tiny-mlm-glue-sst2-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-sst2-target-glue-stsb
  
  This model is a fine-tuned version of [muhtasham/tiny-mlm-glue-sst2](https://huggingface.co/muhtasham/tiny-mlm-glue-sst2) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9195
  - Pearson: 0.8130
  - Spearmanr: 0.8114
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|
  | 2.7776        | 2.78  | 500  | 1.1238          | 0.7313  | 0.7669    |
  | 0.932         | 5.56  | 1000 | 1.0628          | 0.7833  | 0.8086    |
  | 0.737         | 8.33  | 1500 | 1.0050          | 0.8025  | 0.8208    |
  | 0.6099        | 11.11 | 2000 | 0.8592          | 0.8165  | 0.8220    |
  | 0.5164        | 13.89 | 2500 | 0.8875          | 0.8158  | 0.8181    |
  | 0.4659        | 16.67 | 3000 | 0.9524          | 0.8155  | 0.8198    |
  | 0.4114        | 19.44 | 3500 | 0.8872          | 0.8173  | 0.8174    |
  | 0.3728        | 22.22 | 4000 | 0.9423          | 0.8163  | 0.8166    |
  | 0.3396        | 25.0  | 4500 | 0.9953          | 0.8197  | 0.8202    |
  | 0.321         | 27.78 | 5000 | 0.9409          | 0.8160  | 0.8160    |
  | 0.3034        | 30.56 | 5500 | 0.9273          | 0.8142  | 0.8139    |
  | 0.2811        | 33.33 | 6000 | 0.9195          | 0.8130  | 0.8114    |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  