readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - spearmanr
  model-index:
  - name: tiny-mlm-glue-rte-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-rte-target-glue-stsb
  
  This model is a fine-tuned version of [muhtasham/tiny-mlm-glue-rte](https://huggingface.co/muhtasham/tiny-mlm-glue-rte) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9754
  - Pearson: 0.8093
  - Spearmanr: 0.8107
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|
  | 3.2461        | 2.78  | 500  | 1.1464          | 0.7083  | 0.7348    |
  | 1.0093        | 5.56  | 1000 | 1.1455          | 0.7664  | 0.7934    |
  | 0.7582        | 8.33  | 1500 | 1.0140          | 0.7980  | 0.8136    |
  | 0.6329        | 11.11 | 2000 | 0.8708          | 0.8136  | 0.8184    |
  | 0.5285        | 13.89 | 2500 | 0.8894          | 0.8139  | 0.8159    |
  | 0.4747        | 16.67 | 3000 | 0.9908          | 0.8116  | 0.8165    |
  | 0.4154        | 19.44 | 3500 | 0.9260          | 0.8137  | 0.8145    |
  | 0.3792        | 22.22 | 4000 | 0.9264          | 0.8161  | 0.8156    |
  | 0.3445        | 25.0  | 4500 | 0.9664          | 0.8155  | 0.8164    |
  | 0.3246        | 27.78 | 5000 | 0.9735          | 0.8110  | 0.8121    |
  | 0.3033        | 30.56 | 5500 | 0.9754          | 0.8093  | 0.8107    |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  