readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - Gustavosta/Stable-Diffusion-Prompts
  model-index:
  - name: gpt-neo-125M-magicprompt-SD
    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
    top_k: 50
    top_p: 0.95
    repetition_penalty: 5.5
  ---
  
  # gpt-neo-125M-magicprompt-SD
  
  Generate/augment your prompt, stable diffusion style.
  
  This model is a fine-tuned version of [EleutherAI/gpt-neo-125M](https://huggingface.co/EleutherAI/gpt-neo-125M) on the Gustavosta/Stable-Diffusion-Prompts dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.8875
  - perplexity:   6.6028
  
  ## 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: 16
  - eval_batch_size: 2
  - seed: 42
  - distributed_type: multi-GPU
  - num_devices: 2
  - gradient_accumulation_steps: 8
  - total_train_batch_size: 256
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|
  | 3.2189        | 0.99  | 33   | 3.0051          |
  | 2.5466        | 1.99  | 66   | 2.5215          |
  | 2.2791        | 2.99  | 99   | 2.2881          |
  | 2.107         | 3.99  | 132  | 2.1322          |
  | 1.9458        | 4.99  | 165  | 2.0270          |
  | 1.8664        | 5.99  | 198  | 1.9580          |
  | 1.8083        | 6.99  | 231  | 1.9177          |
  | 1.7631        | 7.99  | 264  | 1.8964          |
  | 1.7369        | 8.99  | 297  | 1.8885          |
  | 1.766         | 9.99  | 330  | 1.8875          |
  
  
  ### Framework versions
  
  - Transformers 4.25.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  