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language: en

Model Card for ivila-row-layoutlm-finetuned-s2vl-v2

Model Details

Model Description

  • Developed by: Allen Institute for AI [allenai]
  • Shared by [Optional]: More information needed
  • Model type: Token Classification
  • Language(s) (NLP): en
  • License: More information needed
  • Related Models:
    • Parent Model: LayoutLM
  • Resources for more information:

Uses

Direct Use

This model can be used for the task of Token Classification

Downstream Use [Optional]

More information needed

Out-of-Scope Use

The model should not be used to intentionally create hostile or alienating environments for people.

Bias, Risks, and Limitations

Significant research has explored bias and fairness issues with language models (see, e.g., Sheng et al. (2021) and Bender et al. (2021)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups.

Recommendations

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

Training Details

Training Data

See the LayoutLM model card for more information

LayoutLM was pre-trained on IIT-CDIP Test Collection 1.0* dataset with two settings. LayoutLM-Base, Uncased (11M documents, 2 epochs): 12-layer, 768-hidden, 12-heads, 113M parameters (This Model) LayoutLM-Large, Uncased (11M documents, 2 epochs): 24-layer, 1024-hidden, 16-heads, 343M parameters

Training Procedure

Preprocessing

More information needed

Speeds, Sizes, Times

More information needed

Evaluation

Testing Data, Factors & Metrics

Testing Data

More information needed

Factors

Metrics

More information needed

Results

More information needed

Model Examination

More information needed

Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

  • Hardware Type: More information needed
  • Hours used: More information needed
  • Cloud Provider: More information needed
  • Compute Region: More information needed
  • Carbon Emitted: More information needed

Technical Specifications [optional]

Model Architecture and Objective

More information needed

Compute Infrastructure

More information needed

Hardware

More information needed

Software

  • Transformers_version: 4.6.0

Citation

BibTeX:

@misc{xu2019layoutlm,
   title={LayoutLM: Pre-training of Text and Layout for Document Image Understanding},
   author={Yiheng Xu and Minghao Li and Lei Cui and Shaohan Huang and Furu Wei and Ming Zhou},
   year={2019},
   eprint={1912.13318},
   archivePrefix={arXiv},
   primaryClass={cs.CL}
}

Glossary [optional]

More information needed

More Information [optional]

More information needed

Model Card Authors [optional]

Allen Institute for AI [allenai] in collaboration with Ezi Ozoani and the Hugging Face team

Model Card Contact

More information needed

How to Get Started with the Model

Use the code below to get started with the model.

Click to expand
from transformers import AutoTokenizer, AutoModelForTokenClassification
 
tokenizer = AutoTokenizer.from_pretrained("allenai/ivila-row-layoutlm-finetuned-s2vl-v2")
 
model = AutoModelForTokenClassification.from_pretrained("allenai/ivila-row-layoutlm-finetuned-s2vl-v2")