---
'[object Object]': null
datasets:
- wikiann
language:
- kn
pipeline_tag: token-classification
tags:
- code

widget:
- text: "ನನ್ನ ಹೆಸರು ಅಪರ್ಣ."
  example_title: "Sentence_1"
- text: "ಮೂಲತಃ ನಾನು ಕರ್ನಾಟಕದವಳು."
  example_title: "Sentence_2"
- text: "ನಾನು ಸದ್ಯಕ್ಕೆ ಉನ್ನತ ವ್ಯಾಸಂಗಕ್ಕಾಗಿ ಡಬ್ಲಿನ್ನಲ್ಲಿ ವಾಸವಾಗಿದ್ದೇನೆ. "
  example_title: "Sentence_3"  
- text: "ಅಂಬರೀಶ್ ಈ ಚಲನಚಿತ್ರದ ನಾಯಕರಾಗಿ ಅಭಿನಯಿಸಿ ತುಂಬಾ ಖ್ಯಾತರಾದರು"
  example_title: "Sentence_4"  

---

# Model Card for {{ aparnabhat | default("kannada-ner", true) }}

<!-- Provide a quick summary of what the model is/does. -->

{{ NER using WikiANN dataset }}

# Model Details

## Model Description

<!-- Provide a longer summary of what this model is. -->

{{ model_description  }}

- **Developed by:** {{ Aparna Nayak}}
- **Model type:** {{ NER }}
- **Language(s) (NLP):** {{ Python }}
- **Finetuned from model [optional]:** {{ bert-base-multilingual-cased }}

## Model Sources [optional]

<!-- Provide the basic links for the model. -->

- **Repository:** {{ repo | default("[More Information Needed]", true)}}
<!-- - **Paper [optional]:** {{ paper | default("[More Information Needed]", true)}}
- **Demo [optional]:** {{ demo | default("[More Information Needed]", true)}}  -->

# 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. -->

{{ direct_use | default("[More Information Needed]", true)}}

## Downstream Use [optional]

<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->

{{ downstream_use | default("[More Information Needed]", true)}}

## Out-of-Scope Use

<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->

{{ out_of_scope_use | default("[More Information Needed]", true)}}

# Bias, Risks, and Limitations

<!-- This section is meant to convey both technical and sociotechnical limitations. -->

{{ bias_risks_limitations | default("[More Information Needed]", true)}}

## Recommendations

<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->

{{ 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)}}

# Training Details

## Training Data

<!-- 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. -->

{{ training_data | default("[More Information Needed]", true)}}

## Training Procedure [optional]

<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->

### Preprocessing

{{ preprocessing | default("[More Information Needed]", true)}}

### Speeds, Sizes, Times

<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->

{{ speeds_sizes_times | default("[More Information Needed]", true)}}

# Evaluation

<!-- This section describes the evaluation protocols and provides the results. -->

## Testing Data, Factors & Metrics

### Testing Data

<!-- This should link to a Data Card if possible. -->

{{ testing_data | default("[More Information Needed]", true)}}

### Factors

<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->

{{ testing_factors | default("[More Information Needed]", true)}}

### Metrics

<!-- These are the evaluation metrics being used, ideally with a description of why. -->

{{ testing_metrics | default("[More Information Needed]", true)}}

## Results

{{'LOC': {'precision': 0.5977859778597786,
  'recall': 0.7431192660550459,
  'f1': 0.6625766871165644,
  'number': 218},
 'ORG': {'precision': 0.43333333333333335,
  'recall': 0.34210526315789475,
  'f1': 0.3823529411764707,
  'number': 114},
 'PER': {'precision': 0.4782608695652174,
  'recall': 0.8088235294117647,
  'f1': 0.6010928961748634,
  'number': 136},
 'overall_precision': 0.5262267343485617,
 'overall_recall': 0.6645299145299145,
 'overall_f1': 0.587346553352219,
 'overall_accuracy': 0.8148599269183922}}
 
### Summary

{{ results_summary | default("", true) }}

# Model Examination [optional]

<!-- Relevant interpretability work for the model goes here -->

{{ model_examination | default("[More Information Needed]", true)}}


## Model Architecture and Objective

{{ model_specs | default("[More Information Needed]", true)}}

## Compute Infrastructure

{{ Google colab }}


# Model Card Authors [optional]

{{ Aparna Nayak }}

# Model Card Contact

{{ aparna@iq4.com ; naparnanayak@gmail.com}}

# How to Get Started with the Model

Use the code below to get started with the model.

<details>
<summary> Click to expand </summary>

{{ get_started_code | default("[More Information Needed]", true)}}

</details>