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---
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tags:
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- image-to-text
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- image-captioning
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license: apache-2.0
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metrics:
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- rouge
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datasets:
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- Mozilla/flickr30k-transformed-captions
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widget:
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- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/savanna.jpg
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example_title: Savanna
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- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/football-match.jpg
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example_title: Football Match
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- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/airport.jpg
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example_title: Airport
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base_model:
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- google/vit-base-patch16-224-in21k
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model-index:
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- name: mozilla/distilvit
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results:
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- task:
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type: image-to-text
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name: Image To Text
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dataset:
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name: Mozilla/flickr30k-transformed-captions
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type: Mozilla/flickr30k-transformed-captions
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metrics:
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- name: ROUGE-1
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type: rouge
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value: 43.006
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verified: true
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- name: ROUGE-2
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type: rouge
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value: 16.9939
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verified: true
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- name: ROUGE-L
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type: rouge
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value: 38.8923
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verified: true
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- name: ROUGE-LSUM
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type: rouge
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value: 38.8877
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verified: true
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- name: loss
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type: loss
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value: 0.19939416646957397
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- name: gen_len
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type: gen_len
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value: 11.327256736227712
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verified: true
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---
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# distilvit
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This model is a work in progress. Fine-tuned version of those base models:
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- a VIT model for the image encoder: https://huggingface.co/google/vit-base-patch16-224-in21k
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- a Distilled GPT-2 model for the text decoder: https://huggingface.co/distilbert/distilgpt2
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This model was trained on:
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- [Flickr30k debiased](https://huggingface.co/datasets/Mozilla/flickr30k-transformed-captions-gpt4o)
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- [DocOrNot](https://huggingface.co/datasets/Mozilla/docornot)
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- [Alt Text Validation](https://huggingface.co/datasets/Mozilla/alt-text-validation)
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- A debiased version of COCO 2017: https://cocodataset.org
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You can find the code used to create the model here: https://github.com/mozilla/distilvit
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# training results
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- eval/gen_len 14.99729
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- eval/loss 0.17093
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- eval/meteor 0.51479
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- eval/rouge1 57.8066
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- eval/rouge2 35.0888
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- eval/rougeL 52.9138
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- eval/rougeLsum 52.9101
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- eval/runtime 760.2135
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- eval/samples_per_second 11.18
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- eval/steps_per_second 0.112
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- train/epoch 8.0
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- train/global_step 11752
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- train/learning_rate 0.0
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- train/loss 0.1034
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- train/total_flos 1.518634875573869e+20
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- train/train_loss 0.14875
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- train/train_runtime 91405.9053
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- train/train_samples_per_second 12.855
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- train/train_steps_per_second 0.129
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