Using W&B with the OVH run_common_voice.py script
Run the following in the terminal
# 1. Make sure you have the latest W&B and Transformers from master
pip install git+https://github.com/huggingface/transformers.git
pip install wandb --upgrade

# 2. login to wandb
wandb login

# 3. Set your Project name and Entity (no quotes needed around `wandb` for example) 
export WANDB_ENTITY = wandb
export WANDB_PROJECT = xlsr-french

# 4.  Save your model to W&B (optional)
export WANDB_LOG_MODEL = true 

Now you just have to add  the usual wandb parameters that Trainer needs to the finetune.sh script:
python /workspace/wav2vec/run_common_voice.py \
    --report_to="wandb"
    --run_name = 'fr-baseline',   # Name your run, optional
    --load_best_model_at_end = True, 
    --metric_for_best_model='wer',  
    --greater_is_better=False,
    .....