Add Weights & Biases integration

[rakovskij-stanislav]

This PR adds wandb integration for alpaca_lora_4bit

wandb is an instrument that integrates in torch to make a good training process visualization:

There are visualizations generated by wandb. It helps to:

• compare the difference between runs (the most essential for me is eval/loss) so you can easily experiment with training parameters.
• track your current runs when you are "out from keyboard" (e.g. for watching your torch run on smartphone)
• visualize that your current run is bad (e.g. you tried to reformulate the instruction and it showed worse result) and have a visualized reason to kill this run.
• share your training results with community. It can be good for sharing lora runs. Reports are private by default.
• hardware troubleshooting: wandb visualizes data about your hardware status (power usage, allocated memory, utilization, etc):

Also I found that your code does not use eval dataset at all despite it prepares it: https://github.com/johnsmith0031/alpaca_lora_4bit/blob/main/train_data.py#L166 So every time 20% of dataset was just unused.

[johnsmith0031]

Thanks for your contribution!