readme: ---
  tags:
  - generated_from_trainer
  - stable diffusion
  - beautiful
  - masterpiece
  datasets:
  - Gustavosta/Stable-Diffusion-Prompts
  model-index:
  - name: tiny-gpt2-magicprompt
    results: []
  widget:
   - text: "morning sun over Jakarta"
     example_title: "morning sun"
   - text: "WARNING: pip is"
     example_title: "pip"
   - text: "sentient cheese"
     example_title: "sentient cheese"
   - text: "cheeps are"
     example_title: "cheeps"
  parameters:
    min_length: 32
    max_length: 64
    no_repeat_ngram_size: 1
    do_sample: True
  ---
  
  
  # tiny-gpt2-magicprompt
  
  
  ~~Generate/augment your prompt, stable diffusion style.~~ Enter a new dimension of creativity
  
  This model is a fine-tuned version of [sshleifer/tiny-gpt2](https://huggingface.co/sshleifer/tiny-gpt2) on the Gustavosta/Stable-Diffusion-Prompts dataset.
  It achieves the following results on the evaluation set:
  - Loss: 10.7918
  - perplexity: 48618.8756
  
  ## Intended uses & limitations
  
  ???
  
  ## Training and evaluation data
  
  refer to the `Gustavosta/Stable-Diffusion-Prompts` dataset.
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 0.0001
  - train_batch_size: 8
  - eval_batch_size: 2
  - seed: 42
  - distributed_type: multi-GPU
  - num_devices: 2
  - gradient_accumulation_steps: 32
  - total_train_batch_size: 512
  - total_eval_batch_size: 4
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: cosine
  - lr_scheduler_warmup_ratio: 0.05
  - num_epochs: 10.0
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 10.8201       | 0.96  | 16   | 10.8191         |
  | 10.8167       | 1.96  | 32   | 10.8145         |
  | 10.8117       | 2.96  | 48   | 10.8095         |
  | 10.8058       | 3.96  | 64   | 10.8025         |
  | 10.7997       | 4.96  | 80   | 10.7989         |
  | 10.7959       | 5.96  | 96   | 10.7947         |
  | 10.7934       | 6.96  | 112  | 10.7925         |
  | 10.7924       | 7.96  | 128  | 10.7919         |
  | 10.7921       | 8.96  | 144  | 10.7918         |
  | 10.792        | 9.96  | 160  | 10.7918         |
  
  
  ### Framework versions
  
  - Transformers 4.25.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  