readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - spearmanr
  model-index:
  - name: distilbert_add_GLUE_Experiment_logit_kd_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: .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_add_GLUE_Experiment_logit_kd_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: 1.1264
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
  | 4.3296        | 1.0   | 23   | 3.3387          | nan     | nan       | nan            |
  | 3.9535        | 2.0   | 46   | 3.1277          | nan     | nan       | nan            |
  | 3.7081        | 3.0   | 69   | 2.9189          | nan     | nan       | nan            |
  | 3.4597        | 4.0   | 92   | 2.7125          | nan     | nan       | nan            |
  | 3.2232        | 5.0   | 115  | 2.5114          | nan     | nan       | nan            |
  | 2.972         | 6.0   | 138  | 2.3156          | 0.0070  | 0.0078    | 0.0074         |
  | 2.7373        | 7.0   | 161  | 2.1284          | nan     | nan       | nan            |
  | 2.527         | 8.0   | 184  | 1.9503          | nan     | nan       | nan            |
  | 2.3016        | 9.0   | 207  | 1.7828          | 0.0092  | 0.0081    | 0.0087         |
  | 2.0903        | 10.0  | 230  | 1.6295          | nan     | nan       | nan            |
  | 1.8919        | 11.0  | 253  | 1.4932          | -0.0357 | -0.0358   | -0.0358        |
  | 1.7184        | 12.0  | 276  | 1.3768          | nan     | nan       | nan            |
  | 1.5665        | 13.0  | 299  | 1.2813          | 0.0302  | 0.0292    | 0.0297         |
  | 1.4283        | 14.0  | 322  | 1.2075          | 0.0115  | 0.0132    | 0.0123         |
  | 1.3175        | 15.0  | 345  | 1.1569          | nan     | nan       | nan            |
  | 1.2276        | 16.0  | 368  | 1.1298          | nan     | nan       | nan            |
  | 1.1643        | 17.0  | 391  | 1.1264          | nan     | nan       | nan            |
  | 1.1172        | 18.0  | 414  | 1.1447          | 0.0009  | 0.0027    | 0.0018         |
  | 1.1066        | 19.0  | 437  | 1.1677          | nan     | nan       | nan            |
  | 1.1002        | 20.0  | 460  | 1.1712          | 0.0024  | 0.0003    | 0.0014         |
  | 1.1027        | 21.0  | 483  | 1.1767          | nan     | nan       | nan            |
  | 1.0984        | 22.0  | 506  | 1.1799          | nan     | nan       | nan            |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.14.0a0+410ce96
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  