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Correct documentation

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Jared Nielsen 2020-01-30 13:51:54 -08:00 committed by Lysandre Debut
parent 01a14ebd8d
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examples/README.md
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@ -404,12 +404,12 @@ exact_match = 81.22
#### Distributed training
Here is an example using distributed training on 8 V100 GPUs and Bert Whole Word Masking uncased model to reach a F1 > 93 on SQuAD1.0:
Here is an example using distributed training on 8 V100 GPUs and Bert Whole Word Masking uncased model to reach a F1 > 93 on SQuAD1.1:
```bash
python -m torch.distributed.launch --nproc_per_node=8 run_squad.py \
python -m torch.distributed.launch --nproc_per_node=8 ./examples/run_squad.py \
--model_type bert \
--model_name_or_path bert-base-cased \
--model_name_or_path bert-large-uncased-whole-word-masking \
--do_train \
--do_eval \
--do_lower_case \
@ -419,9 +419,9 @@ python -m torch.distributed.launch --nproc_per_node=8 run_squad.py \
--num_train_epochs 2 \
--max_seq_length 384 \
--doc_stride 128 \
--output_dir ../models/wwm_uncased_finetuned_squad/ \
--per_gpu_train_batch_size 24 \
--gradient_accumulation_steps 12
--output_dir ./examples/models/wwm_uncased_finetuned_squad/ \
--per_gpu_eval_batch_size=3 \
--per_gpu_train_batch_size=3 \
```
Training with the previously defined hyper-parameters yields the following results: