r/MachineLearning· /u/Jumbledsaturn52·· 4 小时前AI 评分27
用 PyTorch 从零实现 2017 版 Transformer 架构
I made Transformer Architecture from scratch [P]
AI 导读
有开发者用 PyTorch 从零实现了 2017 年的 Transformer 架构，但受限于仅 2 层编码器与解码器、1000 词训练数据，模型预测效果不佳。作者表示训练耗时过长，正寻求缩短训练时间或提升效果的方法。
正文
![I made Transformer Architecture from scratch [P]](/api/img-proxy?u=https%3A%2F%2Fexternal-preview.redd.it%2Fe60scNGjES_mYkYPKI3XA-81pS3mfwg7hODdcEVLwwM.png%3Fwidth%3D640%26crop%3Dsmart%26auto%3Dwebp%26s%3D7a9b61fa788b85b55e13df96d523cbcc546c86b5&mode=full&exp=1792972800&sig=508ee72701856e6f "I made Transformer Architecture from scratch [P]") | I implemented the 2017 transformer architecture using pytorch, the model right now doesn't predict very good due to the fact that I am using on 2 layers of encoder and decoder with just 1000 words to train it , due to the fact that it takes a lot of time to train my implementation. Looking at the code is there a way that I can reduce the time it takes for training or maybe improve its results? submitted by /u/Jumbledsaturn52[link] [留言] |
来源：r/MachineLearning · reddit.com