readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - spearmanr
  model-index:
  - name: distilbert_sa_GLUE_Experiment_data_aug_stsb_96
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: GLUE STSB
        type: glue
        args: stsb
      metrics:
      - name: Spearmanr
        type: spearmanr
        value: 0.18181290365831923
  ---
  
  <!-- 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_data_aug_stsb_96
  
  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: 2.7659
  - Pearson: 0.1744
  - Spearmanr: 0.1818
  - Combined Score: 0.1781
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
  | 2.2123        | 1.0   | 1259 | 2.7659          | 0.1744  | 0.1818    | 0.1781         |
  | 0.689         | 2.0   | 2518 | 2.9511          | 0.1794  | 0.1858    | 0.1826         |
  | 0.5239        | 3.0   | 3777 | 2.9043          | 0.1731  | 0.1733    | 0.1732         |
  | 0.4171        | 4.0   | 5036 | 2.9002          | 0.1794  | 0.1788    | 0.1791         |
  | 0.3402        | 5.0   | 6295 | 2.8190          | 0.1899  | 0.1926    | 0.1912         |
  | 0.2843        | 6.0   | 7554 | 2.8391          | 0.1948  | 0.2004    | 0.1976         |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.14.0a0+410ce96
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  