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library_name: transformers
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#
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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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[More Information Needed]
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### Results
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[More Information Needed]
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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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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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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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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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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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# 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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@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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```
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