readme: ---
  language:
  - en
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - spearmanr
  model-index:
  - name: roberta-base-stsb
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: GLUE STSB
        type: glue
        args: stsb
      metrics:
      - name: Spearmanr
        type: spearmanr
        value: 0.907904999413384
  ---
  
  <!-- 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. -->
  
  # roberta-base-stsb
  
  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the GLUE STSB dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4155
  - Pearson: 0.9101
  - Spearmanr: 0.9079
  - Combined Score: 0.9090
  
  ## 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: 2e-05
  - train_batch_size: 16
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.06
  - num_epochs: 10.0
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
  | No log        | 1.0   | 360  | 0.6202          | 0.8787  | 0.8813    | 0.8800         |
  | 1.6425        | 2.0   | 720  | 0.4864          | 0.9008  | 0.8992    | 0.9000         |
  | 0.3629        | 3.0   | 1080 | 0.4201          | 0.9043  | 0.9016    | 0.9030         |
  | 0.3629        | 4.0   | 1440 | 0.4686          | 0.9052  | 0.9003    | 0.9027         |
  | 0.2212        | 5.0   | 1800 | 0.4622          | 0.9061  | 0.9031    | 0.9046         |
  | 0.1556        | 6.0   | 2160 | 0.3952          | 0.9086  | 0.9065    | 0.9075         |
  | 0.1162        | 7.0   | 2520 | 0.4271          | 0.9081  | 0.9070    | 0.9075         |
  | 0.1162        | 8.0   | 2880 | 0.4169          | 0.9094  | 0.9075    | 0.9085         |
  | 0.0887        | 9.0   | 3240 | 0.4383          | 0.9091  | 0.9074    | 0.9083         |
  | 0.0717        | 10.0  | 3600 | 0.4155          | 0.9101  | 0.9079    | 0.9090         |
  
  
  ### Framework versions
  
  - Transformers 4.20.0.dev0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  