readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - spearmanr
  model-index:
  - name: tiny-mlm-snli-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-snli-target-glue-stsb
  
  This model is a fine-tuned version of [muhtasham/tiny-mlm-snli](https://huggingface.co/muhtasham/tiny-mlm-snli) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9081
  - Pearson: 0.8117
  - Spearmanr: 0.8078
  
  ## 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 | Pearson | Spearmanr |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|
  | 3.2807        | 2.78  | 500  | 1.2841          | 0.6694  | 0.6877    |
  | 1.1742        | 5.56  | 1000 | 1.0700          | 0.7574  | 0.7698    |
  | 0.8491        | 8.33  | 1500 | 0.9843          | 0.7918  | 0.7951    |
  | 0.6909        | 11.11 | 2000 | 0.8178          | 0.8113  | 0.8070    |
  | 0.5773        | 13.89 | 2500 | 0.8630          | 0.8127  | 0.8090    |
  | 0.5095        | 16.67 | 3000 | 0.9598          | 0.8122  | 0.8106    |
  | 0.4454        | 19.44 | 3500 | 0.8550          | 0.8159  | 0.8118    |
  | 0.3945        | 22.22 | 4000 | 0.9033          | 0.8122  | 0.8080    |
  | 0.357         | 25.0  | 4500 | 0.9651          | 0.8129  | 0.8091    |
  | 0.3329        | 27.78 | 5000 | 0.9081          | 0.8117  | 0.8078    |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  