--- license: apache-2.0 language: Spanish Nahuatl tags: - translation Spanish Nahuatl --- # t5-small-spanish-nahuatl ## Model description This model is a T5 Transformer ([t5-small](https://huggingface.co/t5-small)) fine-tuned on 29,007 spanish and nahuatl sentences using 12,890 samples collected from the web and 16,117 samples from the Axolotl dataset. The dataset is normalized using 'sep' normalization from [py-elotl](https://github.com/ElotlMX/py-elotl). ## Usage ```python from transformers import AutoModelForSeq2SeqLM from transformers import AutoTokenizer model = AutoModelForSeq2SeqLM.from_pretrained('hackathon-pln-es/t5-small-spanish-nahuatl') tokenizer = AutoTokenizer.from_pretrained('hackathon-pln-es/t5-small-spanish-nahuatl') model.eval() sentence = 'muchas flores son blancas' input_ids = tokenizer('translate Spanish to Nahuatl: ' + sentence, return_tensors='pt').input_ids outputs = model.generate(input_ids) # outputs = miak xochitl istak outputs = tokenizer.batch_decode(outputs, skip_special_tokens=True)[0] ``` ## Evaluation results The model is evaluated on 400 validation sentences. - Validation loss: 1.36 _Note: Since the Axolotl corpus contains multiple misalignments, the real Validation loss is slightly better. These misalignments also introduce noise into the training._ ## References - Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu. 2019. Exploring the limits of transfer learning with a unified Text-to-Text transformer. - Ximena Gutierrez-Vasques, Gerardo Sierra, and Hernandez Isaac. 2016. Axolotl: a web accessible parallel corpus for Spanish-Nahuatl. In International Conference on Language Resources and Evaluation (LREC). ## Team members - Emilio Alejandro Morales [(milmor)](https://huggingface.co/milmor) - Rodrigo Martínez Arzate [(rockdrigoma)](https://huggingface.co/rockdrigoma) - Luis Armando Mercado [(luisarmando)](https://huggingface.co/luisarmando) - Jacobo del Valle [(jjdv)](https://huggingface.co/jjdv)