Update README.md

README.md

@@ -77,7 +77,10 @@ The model was trained on 4 cloud TPUs in Pod configuration (16 TPU chips total)
 of 256. The sequence length was limited to 128 tokens for 90% of the steps and 512 for the remaining 10%. The optimizer
 used is Adam with a learning rate of 1e-4, \\(\beta_{1} = 0.9\\) and \\(\beta_{2} = 0.999\\), a weight decay of 0.01,
 learning rate warmup for 10,000 steps and linear decay of the learning rate after.
-### Fine-tuningAfter pre-training, this model was fine-tuned on the SQuAD dataset with one of our fine-tuning scripts. In order to reproduce the training, you may use the following command:
+
+### Fine-tuning
+
+After pre-training, this model was fine-tuned on the SQuAD dataset with one of our fine-tuning scripts. In order to reproduce the training, you may use the following command:
 ```
 python -m torch.distributed.launch --nproc_per_node=8 ./examples/question-answering/run_qa.py \
     --model_name_or_path bert-large-uncased-whole-word-masking \