readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - spearmanr
  model-index:
  - name: distilbert_sa_GLUE_Experiment_stsb
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: GLUE STSB
        type: glue
        config: stsb
        split: validation
        args: stsb
      metrics:
      - name: Spearmanr
        type: spearmanr
        value: 0.16099086345210553
  ---
  
  <!-- 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. -->
  
  # distilbert_sa_GLUE_Experiment_stsb
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the GLUE STSB dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.3709
  - Pearson: 0.1628
  - Spearmanr: 0.1610
  - Combined Score: 0.1619
  
  ## 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: 5e-05
  - train_batch_size: 256
  - eval_batch_size: 256
  - seed: 10
  - distributed_type: multi-GPU
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 50
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
  | 3.4997        | 1.0   | 23   | 2.5067          | 0.0558  | 0.0619    | 0.0588         |
  | 2.0151        | 2.0   | 46   | 2.4888          | 0.1092  | 0.0973    | 0.1033         |
  | 1.8234        | 3.0   | 69   | 2.3709          | 0.1628  | 0.1610    | 0.1619         |
  | 1.5482        | 4.0   | 92   | 3.0640          | 0.1571  | 0.1632    | 0.1602         |
  | 1.33          | 5.0   | 115  | 3.1306          | 0.1649  | 0.1896    | 0.1772         |
  | 1.1586        | 6.0   | 138  | 2.9752          | 0.1454  | 0.1567    | 0.1511         |
  | 1.0473        | 7.0   | 161  | 3.1783          | 0.1490  | 0.1670    | 0.1580         |
  | 0.9198        | 8.0   | 184  | 3.0440          | 0.1632  | 0.1734    | 0.1683         |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.14.0a0+410ce96
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  