readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - spearmanr
  model-index:
  - name: distilbert_sa_GLUE_Experiment_stsb_384
    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: 0.06351501126231118
  ---
  
  <!-- 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_384
  
  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: 2.3296
  - Pearson: 0.0643
  - Spearmanr: 0.0635
  - Combined Score: 0.0639
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
  | 4.1667        | 1.0   | 23   | 2.3937          | 0.0211  | 0.0215    | 0.0213         |
  | 2.1645        | 2.0   | 46   | 2.3296          | 0.0643  | 0.0635    | 0.0639         |
  | 2.0445        | 3.0   | 69   | 2.5873          | 0.0574  | 0.0760    | 0.0667         |
  | 1.9177        | 4.0   | 92   | 2.5104          | 0.1360  | 0.1374    | 0.1367         |
  | 1.6933        | 5.0   | 115  | 2.4024          | 0.1910  | 0.2072    | 0.1991         |
  | 1.4482        | 6.0   | 138  | 2.5412          | 0.2007  | 0.2127    | 0.2067         |
  | 1.2485        | 7.0   | 161  | 2.5616          | 0.1943  | 0.2005    | 0.1974         |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.14.0a0+410ce96
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  