readme: ---
  license: apache-2.0
  tags:
  - generated-from-trainer
  datasets:
  - julien-c/reactiongif
  metrics:
  - accuracy
  
  model-index:
  - name: model
    results:
    - task:
        name: Text Classification
        type: text-classification
      metrics:
        - name: Accuracy
          type: accuracy
          value: 0.2662102282047272
  ---
  
  <!-- 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. -->
  
  # model
  
  This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on an unkown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.9150
  - Accuracy: 0.2662
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3.0
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 3.0528        | 0.44  | 1000 | 3.0265          | 0.2223   |
  | 2.9836        | 0.89  | 2000 | 2.9263          | 0.2332   |
  | 2.7409        | 1.33  | 3000 | 2.9041          | 0.2533   |
  | 2.7905        | 1.77  | 4000 | 2.8763          | 0.2606   |
  | 2.4359        | 2.22  | 5000 | 2.9072          | 0.2642   |
  | 2.4507        | 2.66  | 6000 | 2.9230          | 0.2644   |
  
  
  ### Framework versions
  
  - Transformers 4.7.0.dev0
  - Pytorch 1.8.1+cu102
  - Datasets 1.8.0
  - Tokenizers 0.10.3
  