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language: ta |
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# TaMillion |
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This is the second version of a Tamil language model trained with |
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Google Research's [ELECTRA](https://github.com/google-research/electra). |
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Tokenization and pre-training CoLab: https://colab.research.google.com/drive/1Pwia5HJIb6Ad4Hvbx5f-IjND-vCaJzSE?usp=sharing |
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V1: small model with GPU; 190,000 steps; |
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V2 (current): base model with TPU and larger corpus; 224,000 steps |
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## Classification |
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Sudalai Rajkumar's Tamil-NLP page contains classification and regression tasks: |
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https://www.kaggle.com/sudalairajkumar/tamil-nlp |
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Notebook: https://colab.research.google.com/drive/1_rW9HZb6G87-5DraxHvhPOzGmSMUc67_?usp=sharin |
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The model outperformed mBERT on news classification: |
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(Random: 16.7%, mBERT: 53.0%, TaMillion: 75.1%) |
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The model slightly outperformed mBERT on movie reviews: |
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(RMSE - mBERT: 0.657, TaMillion: 0.626) |
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Equivalent accuracy on the Tirukkural topic task. |
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## Question Answering |
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I didn't find a Tamil-language question answering dataset, but this model could be finetuned |
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to train a QA model. See Hindi and Bengali examples here: https://colab.research.google.com/drive/1i6fidh2tItf_-IDkljMuaIGmEU6HT2Ar |
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## Corpus |
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Trained on |
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IndicCorp Tamil (11GB) https://indicnlp.ai4bharat.org/corpora/ |
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and 1 October 2020 dump of https://ta.wikipedia.org (482MB) |
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## Vocabulary |
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Included as vocab.txt in the upload |
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