metadata
tags:
- image-to-text
- image-captioning
license: apache-2.0
widget:
- src: >-
https://huggingface.co./datasets/mishig/sample_images/resolve/main/savanna.jpg
example_title: Savanna
- src: >-
https://huggingface.co./datasets/mishig/sample_images/resolve/main/football-match.jpg
example_title: Football Match
- src: >-
https://huggingface.co./datasets/mishig/sample_images/resolve/main/airport.jpg
example_title: Airport
base_model:
- distilbert/distilgpt2
- google/vit-base-patch16-224-in21k
This model is a variation of https://huggingface.co./nlpconnect/vit-gpt2-image-captioning
- Read the blog post here https://ziade.org/2024/03/17/distilvit-image-captioning-model
- The training code is here: https://github.com/tarekziade/distilvit
Results after after 3 epochs (and ~45 hours of training)
- eval_loss: 0.19939416646957397
- eval_rouge1: 43.006
- eval_rouge2: 16.9939
- eval_rougeL: 38.8923
- eval_rougeLsum: 38.8877
- eval_gen_len: 11.327256736227712
- eval_runtime: 1816.5255
- eval_samples_per_second: 13.77
- eval_steps_per_second': 1.721
- train_runtime: 46263.3695
- train_samples_per_second: 38.373
- train_steps_per_second: 4.797
- train_loss: 0.05974134062104816