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_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_sa_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: 1.1255
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
  | 4.2655        | 1.0   | 23   | 3.2719          | 0.0074  | 0.0048    | 0.0061         |
  | 3.8876        | 2.0   | 46   | 3.0839          | -0.0416 | -0.0423   | -0.0420        |
  | 3.6577        | 3.0   | 69   | 2.8849          | nan     | nan       | nan            |
  | 3.4237        | 4.0   | 92   | 2.6822          | 0.0011  | 0.0035    | 0.0023         |
  | 3.1879        | 5.0   | 115  | 2.4766          | nan     | nan       | nan            |
  | 2.9317        | 6.0   | 138  | 2.2745          | 0.0091  | 0.0098    | 0.0094         |
  | 2.6928        | 7.0   | 161  | 2.0801          | 0.0173  | 0.0165    | 0.0169         |
  | 2.4619        | 8.0   | 184  | 1.8985          | -0.0019 | -0.0026   | -0.0023        |
  | 2.2395        | 9.0   | 207  | 1.7302          | nan     | nan       | nan            |
  | 2.0254        | 10.0  | 230  | 1.5798          | nan     | nan       | nan            |
  | 1.8258        | 11.0  | 253  | 1.4485          | nan     | nan       | nan            |
  | 1.6552        | 12.0  | 276  | 1.3382          | -0.0040 | -0.0043   | -0.0041        |
  | 1.511         | 13.0  | 299  | 1.2493          | -0.0376 | -0.0378   | -0.0377        |
  | 1.3781        | 14.0  | 322  | 1.1843          | nan     | nan       | nan            |
  | 1.2754        | 15.0  | 345  | 1.1427          | nan     | nan       | nan            |
  | 1.193         | 16.0  | 368  | 1.1255          | nan     | nan       | nan            |
  | 1.1427        | 17.0  | 391  | 1.1320          | 0.0123  | 0.0102    | 0.0113         |
  | 1.1061        | 18.0  | 414  | 1.1565          | 0.0412  | 0.0370    | 0.0391         |
  | 1.0979        | 19.0  | 437  | 1.1724          | nan     | nan       | nan            |
  | 1.0972        | 20.0  | 460  | 1.1748          | 0.0246  | 0.0255    | 0.0251         |
  | 1.0882        | 21.0  | 483  | 1.1792          | nan     | nan       | nan            |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.14.0a0+410ce96
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  