--- license: apache-2.0 base_model: google/flan-t5-base tags: - generated_from_trainer metrics: - bleu model-index: - name: flan-t5-base-eng-hwp-kjv results: [] language: - en library_name: transformers pipeline_tag: translation --- # flan-t5-base-eng-hwp This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on a English and Hawaiian Pidgin dataset. It achieves the following results on the evaluation set: - Loss: 1.5821 - Bleu: 5.0891 - Gen Len: 18.8633 ## Model description ### Running the model The [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) documentation has more details on running the model. However, to use this model to translate English to Hawaiian Pidgin, enter ``"translate English to Hawaiian Pidgin: "`` before your statement. > For example, if you would like to translate "I went to Ala Moana today to go shopping" please tokenize all of the following: > ``translate English to Hawaiian Pidgin: I went to Ala Moana today to go shopping.`` If you are trying the [English-Hawaiian Pidgin Translator](https://huggingface.co/spaces/claudiatang/english_to_hawaiian-pidgin) space, there is no need for the input prefix, as it is automatically added. ## Training and evaluation data There are not many English-Hawaiian Pidgin parallel corpora that are easily accessible. A parallel dataset, similar to [bible_para](https://huggingface.co/datasets/bible_para), was compiled by scraping the Hawaiʻi Pidgin Version (HWP) and the King James Version (KJV) from [biblegateway.com](https://www.biblegateway.com/). ## Intended uses & limitations Due to a limited set of training and evaluation data, this model has many limitations, such as not knowing certain Hawaiian Pidgin phrases or having trouble with longer sentences. ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0003 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 15 ### Training results | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:| | No log | 1.0 | 420 | 1.6077 | 3.732 | 18.8506 | | 2.1314 | 2.0 | 840 | 1.4572 | 4.2893 | 18.8557 | | 1.5079 | 3.0 | 1260 | 1.3978 | 4.6504 | 18.8599 | | 1.2945 | 4.0 | 1680 | 1.3788 | 4.8595 | 18.8641 | | 1.1387 | 5.0 | 2100 | 1.3841 | 4.907 | 18.8819 | | 1.0142 | 6.0 | 2520 | 1.3776 | 5.0933 | 18.8743 | | 1.0142 | 7.0 | 2940 | 1.3912 | 5.1246 | 18.8726 | | 0.9024 | 8.0 | 3360 | 1.4158 | 5.1468 | 18.8692 | | 0.8227 | 9.0 | 3780 | 1.4403 | 5.1846 | 18.865 | | 0.749 | 10.0 | 4200 | 1.4685 | 5.0892 | 18.8844 | | 0.7012 | 11.0 | 4620 | 1.4997 | 5.1485 | 18.8852 | | 0.6446 | 12.0 | 5040 | 1.5162 | 5.2782 | 18.8776 | | 0.6446 | 13.0 | 5460 | 1.5465 | 5.0961 | 18.8743 | | 0.6063 | 14.0 | 5880 | 1.5588 | 5.0723 | 18.8768 | | 0.5801 | 15.0 | 6300 | 1.5821 | 5.0891 | 18.8633 | ### Framework versions - Transformers 4.34.1 - Pytorch 2.0.1+cu118 - Datasets 2.14.5 - Tokenizers 0.14.1 ## Resources - Christodouloupoulos, C., & Steedman, M. (2014). A massively parallel corpus: the Bible in 100 languages. Language Resources and Evaluation, 49(2), 375–395. https://doi.org/10.1007/s10579-014-9287-y ‌ - Chung, H. W., Hou, L., Longpre, S., Zoph, B., Tay, Y., Fedus, W., … Wei, J. (2022). _Scaling Instruction-Finetuned Language Models._ doi:10.48550/ARXIV.2210.11416 - _Hawaii Pidgin_. (2017). Wycliffe. https://www.biblegateway.com/versions/Hawaii-Pidgin-HWP/ (Original work published 2000) - _King James Bible_. (2017). BibleGateway.com. https://www.biblegateway.com/versions/king-james-version-kjv-bible/ (Original work published 1769) - Translation. (n.d.). Huggingface.co. Retrieved October 18, 2023, from https://huggingface.co/docs/transformers/tasks/translation