readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: xlnet-base-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. -->
  
  # xlnet-base-mnli-fer-finetuned
  
  This model is a fine-tuned version of [clevrly/xlnet-base-mnli-finetuned](https://huggingface.co/clevrly/xlnet-base-mnli-finetuned) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.0152
  - Accuracy: 0.7794
  
  ## 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: 1
  - eval_batch_size: 1
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 4
  - 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 0.5828        | 1.0   | 2219  | 0.9689          | 0.7277   |
  | 0.578         | 2.0   | 4438  | 1.1408          | 0.7310   |
  | 0.5027        | 3.0   | 6657  | 0.9754          | 0.7742   |
  | 0.4233        | 4.0   | 8876  | 1.0719          | 0.7751   |
  | 0.3026        | 5.0   | 11095 | 1.0152          | 0.7794   |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  