dialogpt-tagalog-medium

Tagalog DialoGPT

A DialoGPT-medium model fine-tuned on Tagalog conversational data scraped from the web. This model is an output of a research on RoBERTa-based data augmentation for low resource languages. This is the baseline model which did not use any synthetic data in training.

Latest release: July 25, 2021

• The model is currently only able to respond based on the history of 3 previous utterances before being limited. This is a result of the scarce amount of Tagalog conversations in our dataset.

Dataset

PEx Conversations Dataset

Usage

Here is an example of using beam search for model inference.

for step in range(2): 
    # encode the new user input, add the eos_token and return a tensor in Pytorch
    new_user_input_ids = tokenizer.encode(input(">> User:") + tokenizer.eos_token, return_tensors='pt')

    # append the new user input tokens to the chat history
    bot_input_ids = torch.cat([chat_history_ids, new_user_input_ids], dim=-1) if step > 0 else new_user_input_ids

    # we limit the generation to 512 tokens, each utterance in training had a maximum of 128 tokens
    chat_history_ids = model.generate(
        bot_input_ids, max_length=512,
        pad_token_id=tokenizer.eos_token_id,
        num_beams=5, 
        no_repeat_ngram_size=3
    )
    
    # pretty print last ouput tokens from bot
    print("DialoGPT: {}".format(tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)))

Training Script

Fine-tuning script adapted from Spanish DialoGPT

Research by

• tyadrianpaule
• schuylerng
• dcl127