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@@ -5,7 +5,7 @@ tags:
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  - Document Question Answering
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  - Document Visual Question Answering
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  datasets:
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- - MP-DocVQA
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  language:
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  - en
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  ---
@@ -19,18 +19,6 @@ This model was used as a baseline in [Hierarchical multimodal transformers for M
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  - Results on the MP-DocVQA dataset are reported in Table 2.
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  - Training hyperparameters can be found in Table 8 of Appendix D.
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- ## Model results
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-
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- Extended experimentation can be found in Table 2 of [Hierarchical multimodal transformers for Multi-Page DocVQA](https://arxiv.org/pdf/2212.05935.pdf).
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- You can also check the live leaderboard at the [RRC Portal](https://rrc.cvc.uab.es/?ch=17&com=evaluation&task=4).
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- | Model | HF name | ANLS | APPA |
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- |-----------------------------------------------------------------------------------|:--------------------------------------|:-------------:|:---------:|
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- | [Bert-large](https://huggingface.co/rubentito/bert-large-mpdocvqa) | rubentito/bert-large-mpdocvqa | 0.4183 | 51.6177 |
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- | [Longformer-base](https://huggingface.co/rubentito/longformer-base-mpdocvqa) | rubentito/longformer-base-mpdocvqa | 0.5287 | 71.1696 |
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- | [BigBird ITC base](https://huggingface.co/rubentito/bigbird-base-itc-mpdocvqa) | rubentito/bigbird-base-itc-mpdocvqa | 0.4929 | 67.5433 |
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- | [LayoutLMv3 base](https://huggingface.co/rubentito/layoutlmv3-base-mpdocvqa) | rubentito/layoutlmv3-base-mpdocvqa | 0.4538 | 51.9426 |
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- | [**T5 base**](https://huggingface.co/rubentito/t5-base-mpdocvqa) | rubentito/t5-base-mpdocvqa | 0.5050 | 0.0000 |
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- | Hi-VT5 | TBA | 0.6201 | 79.23 |
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  ## How to use
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@@ -52,6 +40,20 @@ output = self.model.generate(**encoding)
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  answer = tokenizer.decode(output['sequences'], skip_special_tokens=True)
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  ```
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  ## BibTeX entry
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  ```tex
 
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  - Document Question Answering
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  - Document Visual Question Answering
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  datasets:
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+ - rubentito/mp-docvqa
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  language:
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  - en
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  ---
 
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  - Results on the MP-DocVQA dataset are reported in Table 2.
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  - Training hyperparameters can be found in Table 8 of Appendix D.
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  ## How to use
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  answer = tokenizer.decode(output['sequences'], skip_special_tokens=True)
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  ```
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+
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+ ## Model results
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+
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+ Extended experimentation can be found in Table 2 of [Hierarchical multimodal transformers for Multi-Page DocVQA](https://arxiv.org/pdf/2212.05935.pdf).
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+ You can also check the live leaderboard at the [RRC Portal](https://rrc.cvc.uab.es/?ch=17&com=evaluation&task=4).
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+ | Model | HF name | ANLS | APPA |
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+ |-----------------------------------------------------------------------------------|:--------------------------------------|:-------------:|:---------:|
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+ | [Bert-large](https://huggingface.co/rubentito/bert-large-mpdocvqa) | rubentito/bert-large-mpdocvqa | 0.4183 | 51.6177 |
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+ | [Longformer-base](https://huggingface.co/rubentito/longformer-base-mpdocvqa) | rubentito/longformer-base-mpdocvqa | 0.5287 | 71.1696 |
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+ | [BigBird ITC base](https://huggingface.co/rubentito/bigbird-base-itc-mpdocvqa) | rubentito/bigbird-base-itc-mpdocvqa | 0.4929 | 67.5433 |
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+ | [LayoutLMv3 base](https://huggingface.co/rubentito/layoutlmv3-base-mpdocvqa) | rubentito/layoutlmv3-base-mpdocvqa | 0.4538 | 51.9426 |
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+ | [**T5 base**](https://huggingface.co/rubentito/t5-base-mpdocvqa) | rubentito/t5-base-mpdocvqa | 0.5050 | 0.0000 |
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+ | Hi-VT5 | TBA | 0.6201 | 79.23 |
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+
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  ## BibTeX entry
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  ```tex