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  This model is a fine-tuned version of [vidore/colpaligemma-3b-pt-448-base](https://huggingface.co/vidore/colpaligemma-3b-pt-448-base) on the [davanstrien/ufo-ColPali](https://huggingface.co/datasets/davanstrien/ufo-ColPali) dataset.
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- This dataset was created using [Qwen/Qwen2-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2-VL-7B-Instruct). The process for making this dataset is discussed more in the [blog post](https://danielvanstrien.xyz/posts/post-with-code/colpali/2024-09-23-generate_colpali_dataset.html).
 
 
 
 
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  The model achieves the following results on the evaluation set:
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  - Loss: 0.1064
 
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  This model is a fine-tuned version of [vidore/colpaligemma-3b-pt-448-base](https://huggingface.co/vidore/colpaligemma-3b-pt-448-base) on the [davanstrien/ufo-ColPali](https://huggingface.co/datasets/davanstrien/ufo-ColPali) dataset.
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+ The model was trained using the fine tuning [notebook](https://github.com/tonywu71/colpali-cookbooks/blob/main/examples/finetune_colpali.ipynb) from [tonywu71](https://huggingface.co/tonywu71). I changed almost nothing except the data processing steps.
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+ The dataset used for training was created using synthetic data from [Qwen/Qwen2-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2-VL-7B-Instruct). The process for making this dataset is discussed more in the [blog post](https://danielvanstrien.xyz/posts/post-with-code/colpali/2024-09-23-generate_colpali_dataset.html).
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  The model achieves the following results on the evaluation set:
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  - Loss: 0.1064