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update to BERT-large results

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Thomas Wolf 2018-11-11 17:00:49 +01:00 committed by GitHub
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@ -206,7 +206,7 @@ Training with the previous hyper-parameters gave us the following results:
The options we list above allow to fine-tune BERT-large rather easily on GPU(s) instead of the TPU used by the original implementation. The options we list above allow to fine-tune BERT-large rather easily on GPU(s) instead of the TPU used by the original implementation.
For example, fine-tuning BERT-large on SQuAD can be done on a server with 4 k-80 (these are pretty old now) in 18 hours. Our results are similar to the TensorFlow implementation results: For example, fine-tuning BERT-large on SQuAD can be done on a server with 4 k-80 (these are pretty old now) in 18 hours. Our results are similar to the TensorFlow implementation results (actually slightly higher):
```bash ```bash
{"exact_match": 84.56953642384106, "f1": 91.04028647786927} {"exact_match": 84.56953642384106, "f1": 91.04028647786927}
``` ```