Skip to main content

MoverScore: Evaluating text generation with contextualized embeddings and earth mover distance

Project description

MoverScore is a semantic-based evaluation metric for text generation tasks, e.g., machine translation, text summarization, image captioning, question answering and etc, where the system and reference texts are encoded by contextualized word embeddings finetuned on Multi-Natural-Language-Inference, then the Earth Mover Distance is leveraged to compute the semantic distance by comparing two sets of embeddings resp. to the system and reference text

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

moverscore-1.0.3.tar.gz (7.7 kB view details)

Uploaded Source

File details

Details for the file moverscore-1.0.3.tar.gz.

File metadata

  • Download URL: moverscore-1.0.3.tar.gz
  • Upload date:
  • Size: 7.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.15.0 pkginfo/1.4.2 requests/2.18.4 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.30.0 CPython/2.7.15

File hashes

Hashes for moverscore-1.0.3.tar.gz
Algorithm Hash digest
SHA256 99be483d512d4548a2191543f8c7dd6727d83163f92ded2d1958657b177479b8
MD5 bae152b4d93bf5e8429db331d734e0f6
BLAKE2b-256 d7665ac942903a4d2d316f6c1df716e047e34fb0f9bfc7e70d44dab995708e9d

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page