---
license: mit
datasets:
- vrclc/dakshina-lexicons-ml
- vrclc/Dakshina-romanized-ml
- vrclc/Aksharantar-ml
language:
- ml
metrics:
- cer
- wer
- bleu
pipeline_tag: text2text-generation
model-index:
- name: Malayalam Transliteration
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: IndoNLP Test -1 
      type: vrclc/IndoNLP-1
      split: test
      args: ml
    metrics:
    - type: cer
      value: 7.4
      name: CER
---
# Model Card for Model ID

Sequence to Sequence Model for Treansliterationg Romanised Malayalam (Manglish) to Native Script.


### Model Description

- **Developed by:** [Bajiyo Baiju](https://huggingface.co/Bajiyo), [Kavya Manohar](https://huggingface.co/kavyamanohar), [Leena G Pillai](https://huggingface.co/leenag)
- **Language(s) (NLP):** Malayalam
- **License:** MIT

### Model Sources


- **Repository:** https://github.com/VRCLC-DUK/ml-en-transliteration 
- **Paper:** https://arxiv.org/abs/2412.09957
- **Demo:** https://huggingface.co/spaces/vrclc/en-ml-transliteration

## How to Get Started with the Model

The model needs to have an externally defined tokenizers for source and target languages.

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## Training Details

### Training Data

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### Training Procedure

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#### Preprocessing [optional]

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#### Training Hyperparameters

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#### Speeds, Sizes, Times [optional]

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## Evaluation

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### Testing Data, Factors & Metrics

#### Testing Data

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#### Factors

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#### Metrics

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### Results

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#### Summary



## Model Examination [optional]

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## Environmental Impact

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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

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## Technical Specifications [optional]

### Model Architecture and Objective

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#### Hardware

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#### Software

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## Citation [optional]

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