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README.md
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tags:
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---
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---
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'[object Object]': null
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language:
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- en
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library_name: timm
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pipeline_tag: image-classification
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tags:
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- vision
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- mapreader
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- maps
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- National Library of Scotland
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- historical
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- lam
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- humanities
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- heritage
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---
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# Model Card for mr_resnest101e_timm_pretrain
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A ResNeSt (ResNet based architecture with Split Attention) image classification model.
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Trained on gold standard annotations and outputs from early experiments using MapReader (found [here](https://huggingface.co/datasets/Livingwithmachines/MapReader_Data_SIGSPATIAL_2022)).
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## Model Details
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### Model Description
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- **Model type:** Image classification /feature backbone
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- **Finetuned from model:** https://huggingface.co/timm/resnest101e.in1k
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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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{{ direct_use | default("[More Information Needed]", true)}}
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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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{{ downstream_use | default("[More Information Needed]", true)}}
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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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{{ out_of_scope_use | default("[More Information Needed]", true)}}
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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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{{ bias_risks_limitations | default("[More Information Needed]", true)}}
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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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{{ bias_recommendations | default("Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.", true)}}
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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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{{ get_started_code | default("[More Information Needed]", true)}}
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## Training Details
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### Training Data
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<!-- This should link to a Data 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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{{ training_data | default("[More Information Needed]", true)}}
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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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{{ preprocessing | default("[More Information Needed]", true)}}
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#### Training Hyperparameters
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- **Training regime:** {{ training_regime | default("[More Information Needed]", true)}} <!--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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{{ speeds_sizes_times | default("[More Information Needed]", true)}}
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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 Data Card if possible. -->
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{{ testing_data | default("[More Information Needed]", true)}}
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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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{{ testing_factors | default("[More Information Needed]", true)}}
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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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{{ testing_metrics | default("[More Information Needed]", true)}}
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### Results
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{{ results | default("[More Information Needed]", true)}}
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#### Summary
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{{ results_summary | default("", true) }}
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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{{ model_examination | default("[More Information Needed]", true)}}
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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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{{ citation_bibtex | default("[More Information Needed]", true)}}
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**APA:**
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{{ citation_apa | default("[More Information Needed]", true)}}
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## More Information [optional]
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{{ more_information | default("[More Information Needed]", true)}}
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## Model Card Authors [optional]
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{{ model_card_authors | default("[More Information Needed]", true)}}
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## Model Card Contact
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{{ model_card_contact | default("[More Information Needed]", true)}}
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## Funding Statement
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This work was supported by Living with Machines (AHRC grant AH/S01179X/1) and The Alan Turing Institute (EPSRC grant EP/N510129/1).
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Living with Machines, funded by the UK Research and Innovation (UKRI) Strategic Priority Fund, is a multidisciplinary collaboration delivered by the Arts and Humanities Research Council (AHRC), with The Alan Turing Institute, the British Library and Cambridge, King's College London, East Anglia, Exeter, and Queen Mary University of London.
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