Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Finetuning #111

Open
Ehteshamciitwah opened this issue Jul 28, 2023 · 0 comments
Open

Finetuning #111

Ehteshamciitwah opened this issue Jul 28, 2023 · 0 comments

Comments

@Ehteshamciitwah
Copy link

Hello, thank you for sharing your work.

I checked parseq [32,128] pre-trained model for the custom dataset. the sample images are attached. The length of labels ranges from 3 to 20.

However, the word accuracy on the dataset using pre-trained weight is just 56. I fine-tuned your model with default parameters. but it increases to 72% only.

What is the best way to fine-tune your model for the custom dataset?

  1. Input image dimension/patch size
  2. Encoder parameters (layers, head,ratio)
  3. Decoder parameters (layers,head,ratio)
  4. decoding scheme
  5. Permutation K value
  6. Any additional recommendations?

Additionally, how can we integrate a dictionary with the parseq models? i am looking for your response.

imgD-log-0000_1_rotated_0
imgD-log-0000_2_rotated_180
imgD-log-0000_3_rotated_180
imgD-log-0003_1_rotated_0
imgD-log-11-0040_327_rotated_0

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

1 participant