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Small typo fixes for model card: electra-base-german-uncased (#6555)

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* Update README.md

* Update model_cards/german-nlp-group/electra-base-german-uncased/README.md

Co-authored-by: Julien Chaumond <chaumond@gmail.com>
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Philip May 2020-08-18 14:21:52 +02:00 committed by GitHub
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model_cards/german-nlp-group/electra-base-german-uncased/README.md
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@ -20,7 +20,8 @@ This Model is suitable for Training on many downstream tasks in German (Q&A, Sen
It can be used as a drop-in Replacement for **BERT** in most down-stream tasks (**ELECTRA** is even implemented as an extended **BERT** Class).
On the time of the realse (August 2020) this Model is the best performing publicly available German NLP Model on various German Evaluation Metrics (CONLL, GermEval19 Coarse, GermEval19 Fine).
At the time of release (August 2020) this Model is the best performing publicly available German NLP Model on various German Evaluation Metrics (CONLL03-DE, GermEval18 Coarse, GermEval18 Fine). For GermEval18 Coarse results see below. More will be published soon.
## Installation
@ -159,4 +160,3 @@ We tried the following approaches which we found had no positive influence:
- **Increased Vocab Size**: Leads to more parameters and thus reduced examples/sec while no visible Performance gains were measured
- **Decreased Batch-Size**: The original Electra was trained with a Batch Size per TPU Core of 16 whereas this Model was trained with 32 BS / TPU Core. We found out that 32 BS leads to better results when you compare metrics over computation time