[example] add finetune bert with booster example (#3693)

examples/tutorial/new_api/glue_bert/README.md

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+# Finetune BERT on GLUE
+
+## 🚀 Quick Start
+
+This example provides a training script, which provides an example of finetuning BERT on GLUE dataset.
+
+- Training Arguments
+  - `-t`, `--task`: GLUE task to run. Defaults to `mrpc`.
+  - `-p`, `--plugin`: Plugin to use. Choices: `torch_ddp`, `torch_ddp_fp16`, `gemini`, `low_level_zero`. Defaults to `torch_ddp`.
+  - `--target_f1`: Target f1 score. Raise exception if not reached. Defaults to `None`.
+
+
+### Train
+
+```bash
+# train with torch DDP with fp32
+colossalai run --nproc_per_node 4 finetune.py
+
+# train with torch DDP with mixed precision training
+colossalai run --nproc_per_node 4 finetune.py -p torch_ddp_fp16
+
+# train with gemini
+colossalai run --nproc_per_node 4 finetune.py -p gemini
+
+# train with low level zero
+colossalai run --nproc_per_node 4 finetune.py -p low_level_zero
+```
+
+Expected F1-score will be:
+
+| Model             | Single-GPU Baseline FP32 | Booster DDP with FP32 | Booster DDP with FP16 | Booster Gemini | Booster Low Level Zero |
+| ----------------- | ------------------------ | --------------------- | --------------------- |--------------- | ---------------------- |
+| bert-base-uncased | 0.86                     | 0.88                  | 0.87                  | 0.88           | 0.89                   |