This model is a fine-tuned version of distilgpt2 on the ACL-anthology-corpus dataset. It achieves the following results on the evaluation set: — Loss: 3.4835 We finetune the gpt2 LLM on the full-text from ACL-anthology-corpus The following hyperparameters were used during training: — learningrate: 2e-05 — trainbatchsize: 256 — evalbatchsize: 64 — seed: 42 — optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 — lrschedulertype: linear — numepochs: 3 — Transformers 4.21.2 — Pytorch 1.12.1 — Datasets 2.4.0 — Tokenizers 0.12.1 — Prompt : Toward Annotator Grou Introduction — Generation : Toward Annotator Group Bias in Crowdsourcing. Introduction Online platforms for crowdsourcing have received increasing scrutiny in recent years as platforms for online data analytics require an additional layer of content that allows users to interact and be informed about their quality.
Модальности:
Генерация текста
Задача: Генерация текста
Автор: shaurya0512
Теги: gpt2, generated_from_trainer, text-generation-inference, endpoints_compatible
Лайков: 3 | Загрузок: 16
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
