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  ---
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  library_name: transformers
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- tags: []
 
 
 
 
 
 
 
 
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  ---
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- # Model Card for Model ID
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- <!-- Provide a quick summary of what the model is/does. -->
 
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- ## Model Details
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- ### Model Description
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- <!-- Provide a longer summary of what this model is. -->
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- This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- - **Developed by:** [More Information Needed]
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- - **Funded by [optional]:** [More Information Needed]
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- - **Shared by [optional]:** [More Information Needed]
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- - **Model type:** [More Information Needed]
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- - **Language(s) (NLP):** [More Information Needed]
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- - **License:** [More Information Needed]
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- - **Finetuned from model [optional]:** [More Information Needed]
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- ### Model Sources [optional]
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- <!-- Provide the basic links for the model. -->
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- - **Repository:** [More Information Needed]
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- - **Paper [optional]:** [More Information Needed]
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- - **Demo [optional]:** [More Information Needed]
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- ## Uses
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- <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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- ### Direct Use
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- <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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- [More Information Needed]
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- ### Downstream Use [optional]
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- <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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- [More Information Needed]
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- ### Out-of-Scope Use
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- <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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- [More Information Needed]
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- ## Bias, Risks, and Limitations
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- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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- [More Information Needed]
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- ### Recommendations
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- <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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- Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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- ## How to Get Started with the Model
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- Use the code below to get started with the model.
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- [More Information Needed]
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- ## Training Details
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- ### Training Data
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- <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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- [More Information Needed]
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- ### Training Procedure
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- <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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- #### Preprocessing [optional]
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- [More Information Needed]
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- #### Training Hyperparameters
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- - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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- #### Speeds, Sizes, Times [optional]
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- <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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- [More Information Needed]
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- ## Evaluation
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- <!-- This section describes the evaluation protocols and provides the results. -->
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- ### Testing Data, Factors & Metrics
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- #### Testing Data
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- <!-- This should link to a Dataset Card if possible. -->
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- [More Information Needed]
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- #### Factors
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- <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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- [More Information Needed]
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- #### Metrics
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- <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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- ### Results
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- #### Summary
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- ## Model Examination [optional]
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- <!-- Relevant interpretability work for the model goes here -->
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- [More Information Needed]
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- ## Environmental Impact
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- <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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- Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- - **Hardware Type:** [More Information Needed]
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- - **Hours used:** [More Information Needed]
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- - **Cloud Provider:** [More Information Needed]
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- - **Compute Region:** [More Information Needed]
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- - **Carbon Emitted:** [More Information Needed]
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- ## Technical Specifications [optional]
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- ### Model Architecture and Objective
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- ### Compute Infrastructure
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- #### Hardware
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- #### Software
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- ## Citation [optional]
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- <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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  **BibTeX:**
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- **APA:**
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- ## Glossary [optional]
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- <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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- ## More Information [optional]
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- ## Model Card Authors [optional]
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- ## Model Card Contact
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  ---
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  library_name: transformers
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+ tags:
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+ - comics
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+ license: cc-by-sa-4.0
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+ datasets:
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+ - VLR-CVC/ComicsPAP
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+ language:
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+ - en
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+ base_model:
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+ - Qwen/Qwen2.5-VL-7B-Instruct
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  ---
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+ # Lora Fine-Tune of Qwen2.5-VL-3B-Instruct on ComicsPAP datataset
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+ [Qwen2.5-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-7B-Instruct) fine-tunined simultaneously in all five tasks of the [ComicsPAP](https://huggingface.co/datasets/VLR-CVC/ComicsPAP) dataset.
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+ The training was performed using a constant learning rate of 2e-4 with the AdamW optimizer. The model was trained for 5k steps using an effective batch size of 128. The LoRA configuration employed an α of 16, a dropout rate of 0.05, and a rank r = 8.
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+ ## Results
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+ | Model | Repo | Sequence Filling (%) | Character Coherence (%) | Visual Closure (%) | Text Closure (%) | Caption Relevance (%) | Total (%) |
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+ | :------------------------: | :---------------------------------------------------------------------------------: | :------------------: | :---------------------: | :----------------: | :--------------: | :-------------------: | :-------: |
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+ | Random | | 20.22 | 50.00 | 14.41 | 25.00 | 25.00 | 24.30 |
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+ | Qwen2.5-VL-3B (Zero-Shot) | [Qwen/Qwen2.5-VL-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct) | 27.48 | 48.95 | 21.33 | 27.41 | 32.82 | 29.61 |
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+ | Qwen2.5-VL-7B (Zero-Shot) | [Qwen/Qwen2.5-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-7B-Instruct) | 30.53 | 54.55 | 22.00 | 37.45 | 40.84 | 34.91 |
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+ | Qwen2.5-VL-72B (Zero-Shot) | [Qwen/Qwen2.5-VL-72B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-72B-Instruct) | 46.88 | 53.84 | 23.66 | 55.60 | 38.17 | 41.27 |
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+ | Qwen2.5-VL-3B (Lora Fine-Tuned) | [VLR-CVC/Qwen2.5-VL-3B-Instruct-lora-ComicsPAP](https://huggingface.co/VLR-CVC/Qwen2.5-VL-3B-Instruct-lora-ComicsPAP) | 62.21 | **93.01** | **42.33** | 63.71 | 35.49 | 55.55 |
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+ | Qwen2.5-VL-7B (Lora Fine-Tuned) | [VLR-CVC/Qwen2.5-VL-7B-Instruct-lora-ComicsPAP](https://huggingface.co/VLR-CVC/Qwen2.5-VL-7B-Instruct-lora-ComicsPAP) | **69.08** | **93.01** | 42.00 | **74.90** | **49.62** | **62.31** |
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+ ## Citation
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  **BibTeX:**
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+ ```
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+ @misc{vivoli2025comicspap,
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+ title={ComicsPAP: understanding comic strips by picking the correct panel},
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+ author={Emanuele Vivoli and Artemis Llabrés and Mohamed Ali Soubgui and Marco Bertini and Ernest Valveny Llobet and Dimosthenis Karatzas},
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+ year={2025},
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+ eprint={2503.08561},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.CV},
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+ url={https://arxiv.org/abs/2503.08561},
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+ }
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+
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+ @misc{qwen2.5-VL,
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+ title = {Qwen2.5-VL},
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+ url = {https://qwenlm.github.io/blog/qwen2.5-vl/},
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+ author = {Qwen Team},
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+ month = {January},
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+ year = {2025}
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+ }
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+ ```