readme: ---
  license: other
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: dalio-1.3b-test
    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. -->
  
  # dalio-1.3b-test
  
  This model is a fine-tuned version of [facebook/opt-1.3b](https://huggingface.co/facebook/opt-1.3b) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.6035
  - Accuracy: 0.0672
  
  ## 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: 4
  - eval_batch_size: 4
  - seed: 42
  - distributed_type: multi-GPU
  - num_devices: 8
  - total_train_batch_size: 32
  - total_eval_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: cosine
  - num_epochs: 2.0
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 2.6133        | 0.08  | 1    | 2.625           | 0.0652   |
  | 2.6199        | 0.15  | 2    | 2.625           | 0.0652   |
  | 2.7202        | 0.23  | 3    | 2.6113          | 0.0658   |
  | 2.6177        | 0.31  | 4    | 2.6113          | 0.0658   |
  | 2.5422        | 0.38  | 5    | 2.5703          | 0.0661   |
  | 2.5627        | 0.46  | 6    | 2.5566          | 0.0662   |
  | 2.5784        | 0.54  | 7    | 2.5469          | 0.0664   |
  | 2.5264        | 0.62  | 8    | 2.5371          | 0.0663   |
  | 2.3396        | 0.69  | 9    | 2.5332          | 0.0670   |
  | 2.4297        | 0.77  | 10   | 2.5273          | 0.0673   |
  | 2.3914        | 0.85  | 11   | 2.5234          | 0.0672   |
  | 2.429         | 0.92  | 12   | 2.5195          | 0.0671   |
  | 2.3055        | 1.0   | 13   | 2.5117          | 0.0672   |
  | 1.7162        | 1.08  | 14   | 2.5215          | 0.0672   |
  | 1.7264        | 1.15  | 15   | 2.5469          | 0.0677   |
  | 1.7559        | 1.23  | 16   | 2.5879          | 0.0671   |
  | 1.7899        | 1.31  | 17   | 2.6113          | 0.0667   |
  | 1.6465        | 1.38  | 18   | 2.6191          | 0.0666   |
  | 1.5955        | 1.46  | 19   | 2.6074          | 0.0671   |
  | 1.5389        | 1.54  | 20   | 2.5957          | 0.0672   |
  | 1.5356        | 1.62  | 21   | 2.5859          | 0.0670   |
  | 1.386         | 1.69  | 22   | 2.5820          | 0.0672   |
  | 1.7698        | 1.77  | 23   | 2.5742          | 0.0670   |
  | 1.3923        | 1.85  | 24   | 2.5801          | 0.0669   |
  | 1.4723        | 1.92  | 25   | 2.5898          | 0.0672   |
  | 1.5653        | 2.0   | 26   | 2.6035          | 0.0672   |
  
  
  ### Framework versions
  
  - Transformers 4.25.0.dev0
  - Pytorch 1.12.1+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  