readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: roberta-large-mnli-fer-finetuned
    results: []
  ---
  
  <!-- 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. -->
  
  # roberta-large-mnli-fer-finetuned
  
  This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6940
  - Accuracy: 0.5005
  
  ## 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: 2e-05
  - train_batch_size: 1
  - eval_batch_size: 1
  - seed: 42
  - gradient_accumulation_steps: 16
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.7049        | 1.0   | 554  | 0.6895          | 0.5750   |
  | 0.6981        | 2.0   | 1108 | 0.7054          | 0.5005   |
  | 0.7039        | 3.0   | 1662 | 0.6936          | 0.5005   |
  | 0.6976        | 4.0   | 2216 | 0.6935          | 0.4995   |
  | 0.6991        | 5.0   | 2770 | 0.6940          | 0.5005   |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  