readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - accuracy
  model-index:
  - name: canine-c-finetuned-sst2
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: glue
        type: glue
        args: sst2
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.8486238532110092
  ---
  
  <!-- 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. -->
  
  # canine-c-finetuned-sst2
  
  This model is a fine-tuned version of [google/canine-c](https://huggingface.co/google/canine-c) on the glue dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6025
  - Accuracy: 0.8486
  
  ## 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: 4.9121586874695155e-05
  - train_batch_size: 32
  - eval_batch_size: 16
  - seed: 8
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 4
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.3415        | 1.0   | 2105 | 0.4196          | 0.8280   |
  | 0.2265        | 2.0   | 4210 | 0.4924          | 0.8211   |
  | 0.1439        | 3.0   | 6315 | 0.5726          | 0.8337   |
  | 0.0974        | 4.0   | 8420 | 0.6025          | 0.8486   |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  