
Machine Translation on WMT2014 English-German
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MODEL
REPOSITORY
BLEU SCORE | SACREBLEU | SPEED |
PAPER
ε-REPRODUCES PAPER
Models on Papers with Code
for which code has not been tried out yet.
This benchmark is evaluating models on the test set of the WMT 2014 English-German news (full) dataset.
Step 1: Evaluate models locally
First, use our public benchmark library to evaluate your model. sotabench-eval
is a framework-agnostic library that implements the WMT2014 Benchmark. See sotabench-eval docs here.
Once you can run the benchmark locally, you are ready to connect it to our automatic service.
Step 2: Login and connect your GitHub Repository
Connect your GitHub repository to automatically start benchmarking your repository. Once connected we'll re-benchmark your master
branch on every commit, giving your users confidence in using models in your repository and helping you spot any bugs.