Edit model card

opt-350m-magicprompt-SD

Generate/augment your prompt, stable diffusion style.

This model is a fine-tuned version of facebook/opt-350m on the Gustavosta/Stable-Diffusion-Prompts dataset. It achieves the following results on the evaluation set:

  • Loss: 1.2987
  • eval_steps_per_second = 16.623
  • perplexity = 3.6644

example

jakarta

output (on DALL-E 2, but as words are words, works anywhere)

dalle2-jakarta

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
2.8568 0.95 16 2.5937
2.2487 1.95 32 2.1050
1.9011 2.95 48 1.8082
1.6837 3.95 64 1.6178
1.4887 4.95 80 1.4897
1.3812 5.95 96 1.4017
1.2944 6.95 112 1.3437
1.2574 7.95 128 1.3127
1.2325 8.95 144 1.3009
1.2223 9.95 160 1.2987

Framework versions

  • Transformers 4.25.0.dev0
  • Pytorch 1.13.0+cu117
  • Datasets 2.6.1
  • Tokenizers 0.13.1
Downloads last month
9
Safetensors
Model size
331M params
Tensor type
F32
·

Finetuned from

Dataset used to train pszemraj/opt-350m-magicprompt-SD