Restore README.md to commit b261205

README.md

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 ---
+license: apache-2.0
+base_model:
+- timm/eva02_large_patch14_448.mim_m38m_ft_in22k_in1k
+library_name: fastai
 tags:
-- fastai
+- Coleoptera
+- Taxonomy
+- Biology
+- Cicindelidae
 ---
 
-# Amazing!
+# Model Card for Model ID
 
-🥳 Congratulations on hosting your fastai model on the Hugging Face Hub!
+<!-- Provide a quick summary of what the model is/does. -->
 
-# Some next steps
-1. Fill out this model card with more information (see the template below and the [documentation here](https://huggingface.co/docs/hub/model-repos))!
+This model was trained on all specimens of *Cicindela* tiger beetles from the Field Museum. It is a multilabel model able to identify species and subspecies. See the model config file for all labels included and the publication for metrics.
 
-2. Create a demo in Gradio or Streamlit using 🤗 Spaces ([documentation here](https://huggingface.co/docs/hub/spaces)).
+## Model Details
 
-3. Join the fastai community on the [Fastai Discord](https://discord.com/invite/YKrxeNn)!
+This model is based on the pre-trained [eva02_large_patch14_448](https://huggingface.co/timm/eva02_large_patch14_448.mim_m38m_ft_in22k_in1k) from the timm library.
 
-Greetings fellow fastlearner 🤝! Don't forget to delete this content from your model card.
+The training included several tricks to allow multilabel training with an imbalanced dataset, see the publication for details.
 
 
----
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** Bruno A. S. de Medeiros, Negaunee Assistant Curator of Pollinating Insects, Field Museum.
+- **Model type:** Image classification
+- **License:** Apache 2.0
+- **Finetuned from model [optional]:** [eva02_large_patch14_448](https://huggingface.co/timm/eva02_large_patch14_448.mim_m38m_ft_in22k_in1k)
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Paper [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+Identification of pinned *Cicindela* specimens.
+
+
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+This model will fail to make predictions on species not present in the FMNH collection. It is also unlikely to perform well for specimens that are note pinned.
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+The model is only expected to perform well for images of pinned tiger beetles.
+
+
+## Training Details
+
+### Training Data
+
+<!-- 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. -->
+
+Data generated by Elizabeth Postema using DrawerDissect on Field Museum specimens, see the publication for details.
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** fp16 mixed precision
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+A subset of the specimens was held as a test set. See publication for details
+
+
+#### Metrics
+
+Metrics in the test set:
+
+Dataset Overview:
+- Total taxa analyzed: 193
+- Species: 115 (59.6%)
+- Subspecies: 78 (40.4%)
+
+Performance Summary:
+
+Species:
+- Specimen-weighted precision: 96.8%
+- Specimen-weighted recall: 80.9%
+- Specimen-weighted precision: 97.0%
+- Specimen-weighted recall: 96.4%
+
+Subspecies:
+- Specimen-weighted precision: 89.0%
+- Specimen-weighted recall: 66.5%
+- Specimen-weighted precision: 85.0%
+- Specimen-weighted recall: 89.0%
+
+
+
+## Citation 
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
 
+**APA:**
 
-# Model card
+[More Information Needed]
 
-## Model description
-More information needed
 
-## Intended uses & limitations
-More information needed
+## Model Card Authors
 
-## Training and evaluation data
-More information needed
+Bruno de Medeiros, Negaunee Assistant Curator of Pollinating Insects, Field Museum