readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - spearmanr
  model-index:
  - name: distilbert_sa_GLUE_Experiment_logit_kd_stsb_256
    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: .nan
  ---
  
  <!-- 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_logit_kd_stsb_256
  
  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: 1.1268
  - Pearson: nan
  - Spearmanr: nan
  - Combined Score: nan
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
  | 3.1622        | 1.0   | 23   | 1.7502          | -0.0248 | -0.0193   | -0.0221        |
  | 1.8579        | 2.0   | 46   | 1.3087          | -0.0465 | -0.0476   | -0.0470        |
  | 1.3508        | 3.0   | 69   | 1.1268          | nan     | nan       | nan            |
  | 1.1078        | 4.0   | 92   | 1.1974          | 0.0294  | 0.0287    | 0.0290         |
  | 1.0747        | 5.0   | 115  | 1.1797          | 0.0509  | 0.0597    | 0.0553         |
  | 1.024         | 6.0   | 138  | 1.2292          | 0.0554  | 0.0782    | 0.0668         |
  | 0.944         | 7.0   | 161  | 1.2819          | 0.1274  | 0.1441    | 0.1358         |
  | 0.795         | 8.0   | 184  | 1.2143          | 0.1987  | 0.2082    | 0.2035         |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.14.0a0+410ce96
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  