readme: ---
  license: other
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: opt-model
    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. -->
  
  # opt-model
  
  This model is a fine-tuned version of [facebook/opt-13b](https://huggingface.co/facebook/opt-13b) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.3965
  - Accuracy: 0.5020
  
  ## 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: 1e-05
  - train_batch_size: 24
  - eval_batch_size: 24
  - seed: 42
  - distributed_type: multi-GPU
  - num_devices: 3
  - total_train_batch_size: 72
  - total_eval_batch_size: 72
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5.0
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 3.6363        | 1.0   | 3    | 3.2090          | 0.4082   |
  | 2.8168        | 2.0   | 6    | 2.4805          | 0.4874   |
  | 2.3529        | 3.0   | 9    | 2.4219          | 0.4915   |
  | 2.1842        | 4.0   | 12   | 2.4023          | 0.4991   |
  | 2.0765        | 5.0   | 15   | 2.3965          | 0.5020   |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.0+cu102
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  