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README.md
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- **Dataset** - 1M data samples are used to train this model from OSCAR page(https://oscar-corpus.com/) eventhough data set is of 2.7 GB due to resource constraint to train
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I have picked only 1M data from the total 2.7GB data set. If you are interested in collaboration and have computational resources to train on you are most welcome to do so.
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- **Preprocessing** - ByteLevelBPETokenizer is used to tokenize the sentences at character level and vocabulary size is set to 52k as per standard values given by
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<!-- - **Hyperparameters** - __ByteLevelBPETokenizer__ : vocabulary size = 52_000 and min_frequency = 2
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__Trainer__ : num_train_epochs=12 - trained for 12 epochs
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per_gpu_train_batch_size=64 - batch size for the datasamples is 64
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@@ -25,4 +25,4 @@ I have picked only 1M data from the total 2.7GB data set. If you are interested
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this is for anyone who wants to make use of marathi language models for various tasks like language generation, translation and many more use cases.
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**Whatever else is helpful!**
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If you are intersted in collaboration feel free to reach me [Deepam](mailto:deepam8155@gmail.com)
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- **Dataset** - 1M data samples are used to train this model from OSCAR page(https://oscar-corpus.com/) eventhough data set is of 2.7 GB due to resource constraint to train
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15 |
I have picked only 1M data from the total 2.7GB data set. If you are interested in collaboration and have computational resources to train on you are most welcome to do so.
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- **Preprocessing** - ByteLevelBPETokenizer is used to tokenize the sentences at character level and vocabulary size is set to 52k as per standard values given by 🤗
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<!-- - **Hyperparameters** - __ByteLevelBPETokenizer__ : vocabulary size = 52_000 and min_frequency = 2
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__Trainer__ : num_train_epochs=12 - trained for 12 epochs
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per_gpu_train_batch_size=64 - batch size for the datasamples is 64
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this is for anyone who wants to make use of marathi language models for various tasks like language generation, translation and many more use cases.
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**Whatever else is helpful!**
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+
If you are intersted in collaboration feel free to reach me [Deepam](mailto:deepam8155@gmail.com)
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