readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: finetuning_results
    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. -->
  
  # finetuning_results
  
  This model is a fine-tuned version of [DanielSM/finetuning_results](https://huggingface.co/DanielSM/finetuning_results) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0000
  - Accuracy: 1.0
  
  ## 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: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 12
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.0555        | 1.0   | 50   | 0.0003          | 1.0      |
  | 0.0064        | 2.0   | 100  | 0.0001          | 1.0      |
  | 0.002         | 3.0   | 150  | 0.0000          | 1.0      |
  | 0.0027        | 4.0   | 200  | 0.0000          | 1.0      |
  | 0.0001        | 5.0   | 250  | 0.0000          | 1.0      |
  | 0.0001        | 6.0   | 300  | 0.0000          | 1.0      |
  | 0.0001        | 7.0   | 350  | 0.0000          | 1.0      |
  | 0.0001        | 8.0   | 400  | 0.0000          | 1.0      |
  | 0.0001        | 9.0   | 450  | 0.0000          | 1.0      |
  | 0.0001        | 10.0  | 500  | 0.0000          | 1.0      |
  | 0.0001        | 11.0  | 550  | 0.0000          | 1.0      |
  | 0.0001        | 12.0  | 600  | 0.0000          | 1.0      |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  