readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - spearmanr
  model-index:
  - name: distilbert_sa_GLUE_Experiment_stsb_96
    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: 0.01641373482271163
  ---
  
  <!-- 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_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: 2.2501
  - Pearson: 0.0145
  - Spearmanr: 0.0164
  - Combined Score: 0.0154
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
  | 8.5764        | 1.0   | 23   | 6.5600          | -0.0093 | -0.0112   | -0.0102        |
  | 7.7973        | 2.0   | 46   | 6.1824          | 0.0235  | 0.0229    | 0.0232         |
  | 7.3288        | 3.0   | 69   | 5.7819          | -0.0634 | -0.0621   | -0.0628        |
  | 6.8588        | 4.0   | 92   | 5.3627          | nan     | nan       | nan            |
  | 6.3722        | 5.0   | 115  | 4.9405          | nan     | nan       | nan            |
  | 5.8419        | 6.0   | 138  | 4.5257          | 0.0099  | 0.0107    | 0.0103         |
  | 5.3405        | 7.0   | 161  | 4.1302          | nan     | nan       | nan            |
  | 4.8794        | 8.0   | 184  | 3.7607          | nan     | nan       | nan            |
  | 4.4156        | 9.0   | 207  | 3.4218          | -0.0075 | -0.0067   | -0.0071        |
  | 3.991         | 10.0  | 230  | 3.1190          | 0.0246  | 0.0246    | 0.0246         |
  | 3.6029        | 11.0  | 253  | 2.8558          | -0.0034 | -0.0006   | -0.0020        |
  | 3.2636        | 12.0  | 276  | 2.6377          | nan     | nan       | nan            |
  | 2.9656        | 13.0  | 299  | 2.4660          | 0.0137  | 0.0129    | 0.0133         |
  | 2.7028        | 14.0  | 322  | 2.3432          | nan     | nan       | nan            |
  | 2.4851        | 15.0  | 345  | 2.2710          | 0.0132  | 0.0145    | 0.0138         |
  | 2.3576        | 16.0  | 368  | 2.2501          | 0.0145  | 0.0164    | 0.0154         |
  | 2.2531        | 17.0  | 391  | 2.2773          | nan     | nan       | nan            |
  | 2.2045        | 18.0  | 414  | 2.3342          | -0.0082 | -0.0113   | -0.0098        |
  | 2.1967        | 19.0  | 437  | 2.3460          | nan     | nan       | nan            |
  | 2.2041        | 20.0  | 460  | 2.3556          | -0.0025 | -0.0010   | -0.0017        |
  | 2.1816        | 21.0  | 483  | 2.3715          | 0.0142  | 0.0160    | 0.0151         |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.14.0a0+410ce96
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  