PreTrain T5 from scratch in Bengali

T5 for Bengali

Currently, there is no T5 model that was trained from scratch for Bengali on the hub. For this project, the goal is to create a strong language generation model for Bengali using T5 Model.

2. Language


3. Model

A randomly initialized T5 model.

4. Datasets

One can make use of OSCAR the dataset is also available through the datasets library here: oscar · Datasets at Hugging Face. The total Bengali resource in OSCAR is 11 GB.

Another source can be the mC4 dataset which is available in AllenAI. The resource size is 29GB.

5. Training scripts

A causal language modeling script for Flax is available here. It can be tweaked for training T5.

6. Challenges

  • Adapt the training script to T5
  • Fix a good tokenizer that covers Bengali vocabulary properly and make sure that the LM doesn’t become character-level LM.

7. Desired project outcome

The desired project output is a T5 model that is able to generate Bengali language.

8. Reads

The most important read would be the following colab:

Apart from that we may need to look at the seqio library and source code of T5 here,


I am also a Bengali speaker. I am in!

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Sounds great, let’s finalize it!

Any update on this? Is there a repo for this project?

@sbmaruf any update on this ? were you able to use seqio for T5 in the huggingface training script ?

We trained T5 with hggingface flax script, but the performance of the the language model on downstream task was very poor.

With the same data, the causal model worked fine.

More on T5 convergence issues I found later on.