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End of training

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  1. README.md +8 -8
  2. checkpoint-100000/optimizer.bin +3 -0
  3. checkpoint-100000/random_states_0.pkl +3 -0
  4. checkpoint-100000/scaler.pt +3 -0
  5. checkpoint-100000/scheduler.bin +3 -0
  6. checkpoint-100000/unet/config.json +65 -0
  7. checkpoint-100000/unet/diffusion_pytorch_model.bin +3 -0
  8. checkpoint-110000/optimizer.bin +3 -0
  9. checkpoint-110000/random_states_0.pkl +3 -0
  10. checkpoint-110000/scaler.pt +3 -0
  11. checkpoint-110000/scheduler.bin +3 -0
  12. checkpoint-110000/unet/config.json +65 -0
  13. checkpoint-110000/unet/diffusion_pytorch_model.bin +3 -0
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  15. checkpoint-120000/random_states_0.pkl +3 -0
  16. checkpoint-120000/scaler.pt +3 -0
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  18. checkpoint-120000/unet/config.json +65 -0
  19. checkpoint-120000/unet/diffusion_pytorch_model.bin +3 -0
  20. checkpoint-60000/optimizer.bin +3 -0
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  24. checkpoint-60000/unet/config.json +65 -0
  25. checkpoint-60000/unet/diffusion_pytorch_model.bin +3 -0
  26. checkpoint-80000/optimizer.bin +3 -0
  27. checkpoint-80000/random_states_0.pkl +3 -0
  28. checkpoint-80000/scaler.pt +3 -0
  29. checkpoint-80000/scheduler.bin +3 -0
  30. checkpoint-80000/unet/config.json +65 -0
  31. checkpoint-80000/unet/diffusion_pytorch_model.bin +3 -0
  32. checkpoint-90000/optimizer.bin +3 -0
  33. checkpoint-90000/random_states_0.pkl +3 -0
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  35. checkpoint-90000/scheduler.bin +3 -0
  36. checkpoint-90000/unet/config.json +65 -0
  37. checkpoint-90000/unet/diffusion_pytorch_model.bin +3 -0
  38. model_index.json +2 -1
  39. scheduler/scheduler_config.json +1 -1
  40. unet/config.json +2 -2
  41. unet/diffusion_pytorch_model.bin +1 -1
  42. vae/config.json +2 -1
  43. val_imgs_grid.png +0 -0
README.md CHANGED
@@ -3,7 +3,7 @@
3
  license: creativeml-openrail-m
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  base_model: runwayml/stable-diffusion-v1-5
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  datasets:
6
- - iamkaikai/amazing_logos
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  tags:
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  - stable-diffusion
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  - stable-diffusion-diffusers
@@ -14,7 +14,7 @@ inference: true
14
 
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  # Text-to-image finetuning - iamkaikai/amazing-logos
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- This pipeline was finetuned from **runwayml/stable-diffusion-v1-5** on the **iamkaikai/amazing_logos** dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['Simple elegant logo for a Digital Art, D A Circle, successful vibe, minimalist, thought-provoking, abstract, recognizable']:
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  ![val_imgs_grid](./val_imgs_grid.png)
20
 
@@ -28,7 +28,7 @@ from diffusers import DiffusionPipeline
28
  import torch
29
 
30
  pipeline = DiffusionPipeline.from_pretrained("iamkaikai/amazing-logos", torch_dtype=torch.float16)
31
- prompt = "Simple elegant logo for a Digital Art, D A Circle, successful vibe, minimalist, thought-provoking, abstract, recognizable"
32
  image = pipeline(prompt).images[0]
33
  image.save("my_image.png")
34
  ```
@@ -37,12 +37,12 @@ image.save("my_image.png")
37
 
38
  These are the key hyperparameters used during training:
39
 
40
- * Epochs: 60
41
- * Learning rate: 1e-05
42
- * Batch size: 20
43
- * Gradient accumulation steps: 16
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  * Image resolution: 512
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  * Mixed-precision: fp16
46
 
47
 
48
- More information on all the CLI arguments and the environment are available on your [`wandb` run page](https://wandb.ai/iam-kai-kai/text2image-fine-tune/runs/9soqeiq6).
 
3
  license: creativeml-openrail-m
4
  base_model: runwayml/stable-diffusion-v1-5
5
  datasets:
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+ - iamkaikai/amazing_logos_v2
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  tags:
8
  - stable-diffusion
9
  - stable-diffusion-diffusers
 
14
 
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  # Text-to-image finetuning - iamkaikai/amazing-logos
16
 
17
+ This pipeline was finetuned from **runwayml/stable-diffusion-v1-5** on the **iamkaikai/amazing_logos_v2** dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['Simple elegant logo for Digital Art, D A Square Symmetrical, successful vibe, minimalist, thought-provoking, abstract, recognizable, black and white']:
18
 
19
  ![val_imgs_grid](./val_imgs_grid.png)
20
 
 
28
  import torch
29
 
30
  pipeline = DiffusionPipeline.from_pretrained("iamkaikai/amazing-logos", torch_dtype=torch.float16)
31
+ prompt = "Simple elegant logo for Digital Art, D A Square Symmetrical, successful vibe, minimalist, thought-provoking, abstract, recognizable, black and white"
32
  image = pipeline(prompt).images[0]
33
  image.save("my_image.png")
34
  ```
 
37
 
38
  These are the key hyperparameters used during training:
39
 
40
+ * Epochs: 12
41
+ * Learning rate: 1e-07
42
+ * Batch size: 1
43
+ * Gradient accumulation steps: 1
44
  * Image resolution: 512
45
  * Mixed-precision: fp16
46
 
47
 
48
+ More information on all the CLI arguments and the environment are available on your [`wandb` run page](https://wandb.ai/iam-kai-kai/text2image-fine-tune/runs/0av1w9qj).
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