Dataset Language Modelling on WikiText-103

Language Modelling on WikiText-103

#
MODEL
REPOSITORY
TEST PERPLEXITY SPEED
PAPER
ε-REPRODUCES PAPER
1
16.44 483.6
2
18.19 2970.8
3
18.70 1685.4
4
22.61 4482.9
5
26.51 9316.7
6
36.53 25200.1
7
49.91 38425.0
--
8
90.61 29444.9
--
Models on Papers with Code for which code has not been tried out yet.
MODEL
PAPER
TEST PERPLEXITY VALIDATION PERPLEXITY

This benchmark is evaluating language models on the WikiText-103 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 WikiText-103 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.