Update README.md

README.md

@@ -24,22 +24,27 @@ The only difference is that there are a few new training arguments specific to H
 
 [Here](https://github.com/huggingface/optimum-habana/blob/main/examples/question-answering/run_qa.py) is a question-answering example script to fine-tune a model on SQuAD. You can run it with ALBERT XXL with the following command:
 ```bash
-python run_qa.py \
+PT_HPU_LAZY_MODE=0 PT_ENABLE_INT64_SUPPORT=1 python run_qa.py \
   --model_name_or_path albert-xxlarge-v1 \
-  --gaudi_config_name Habana/albert-xxlarge-v1 \
+  --gaudi_config_name Habana/albert-xxlarge-v1
   --dataset_name squad \
   --do_train \
   --do_eval \
-  --per_device_train_batch_size 12 \
+  --per_device_train_batch_size 16 \
   --per_device_eval_batch_size 2 \
-  --learning_rate 5e-6 \
+  --learning_rate 7e-05 \
   --num_train_epochs 2 \
   --max_seq_length 384 \
   --output_dir /tmp/squad/ \
   --use_habana \
-  --use_lazy_mode \
+  --use_lazy_mode false \
+  --torch_compile \
+  --torch_compile_backend hpu_backend \
   --throughput_warmup_steps 3 \
-  --bf16
+  --bf16 \
+  --save_strategy no \
+  --doc_stride 128 \
+  --overwrite_output_di
 ```
 
 Check the [documentation](https://huggingface.co/docs/optimum/habana/index) out for more advanced usage and examples.