readme: ---
  license: other
  tags:
  - generated_from_trainer
  datasets:
  - AlekseyKorshuk/dalio-synthetic-io
  metrics:
  - accuracy
  model-index:
  - name: dalio-synthetic-io-1.3b
    results:
    - task:
        name: Causal Language Modeling
        type: text-generation
      dataset:
        name: AlekseyKorshuk/dalio-synthetic-io
        type: AlekseyKorshuk/dalio-synthetic-io
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.06357949136406908
  ---
  
  <!-- 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-synthetic-io-1.3b
  
  This model is a fine-tuned version of [facebook/opt-1.3b](https://huggingface.co/facebook/opt-1.3b) on the AlekseyKorshuk/dalio-synthetic-io dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.4961
  - Accuracy: 0.0636
  
  ## 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: 3e-05
  - train_batch_size: 2
  - eval_batch_size: 2
  - seed: 42
  - distributed_type: multi-GPU
  - num_devices: 8
  - total_train_batch_size: 16
  - total_eval_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: cosine
  - num_epochs: 1.0
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 2.6941        | 0.05  | 1    | 2.6543          | 0.0622   |
  | 2.6914        | 0.11  | 2    | 2.6543          | 0.0622   |
  | 2.6003        | 0.16  | 3    | 2.6016          | 0.0627   |
  | 2.5603        | 0.21  | 4    | 2.5703          | 0.0626   |
  | 2.606         | 0.26  | 5    | 2.5508          | 0.0629   |
  | 2.5439        | 0.32  | 6    | 2.5449          | 0.0629   |
  | 2.4449        | 0.37  | 7    | 2.5469          | 0.0629   |
  | 2.5422        | 0.42  | 8    | 2.5469          | 0.0630   |
  | 2.6101        | 0.47  | 9    | 2.5410          | 0.0632   |
  | 2.4482        | 0.53  | 10   | 2.5352          | 0.0630   |
  | 2.501         | 0.58  | 11   | 2.5293          | 0.0631   |
  | 2.5967        | 0.63  | 12   | 2.5215          | 0.0634   |
  | 2.4998        | 0.68  | 13   | 2.5137          | 0.0635   |
  | 2.5957        | 0.74  | 14   | 2.5098          | 0.0636   |
  | 2.5967        | 0.79  | 15   | 2.5039          | 0.0639   |
  | 2.5022        | 0.84  | 16   | 2.5             | 0.0637   |
  | 2.4314        | 0.89  | 17   | 2.4980          | 0.0637   |
  | 2.6279        | 0.95  | 18   | 2.4961          | 0.0636   |
  | 2.571         | 1.0   | 19   | 2.4961          | 0.0636   |
  
  
  ### Framework versions
  
  - Transformers 4.25.0.dev0
  - Pytorch 1.12.1+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  