Process:
- created a distil-whisper model trained on cv_13 nl. Afterwards finetuned the model with the following parameters on mac m1 max (32gb)

Results:
- eval_loss 0.1334582418203354
- eval_wer 13.924597710391687

from transformers import Seq2SeqTrainingArguments

training_args = Seq2SeqTrainingArguments(
    output_dir="./whisper-small-student-ft-nl",  # change to a repo name of your choice
    per_device_train_batch_size=16,
    gradient_accumulation_steps=1,  # increase by 2x for every 2x decrease in batch size
    learning_rate=1e-5,
    warmup_steps=500,
    max_steps=4000,
    gradient_checkpointing=True,
    fp16=False,
    evaluation_strategy="steps",
    per_device_eval_batch_size=8,
    predict_with_generate=True,
    generation_max_length=225,
    save_steps=1000,
    eval_steps=1000,
    logging_steps=25,
    report_to=["tensorboard"],
    load_best_model_at_end=True,
    metric_for_best_model="wer",
    greater_is_better=False,
    push_to_hub=True,
    do_train=False,
)

{"language": ["nl"], "datasets": ["mozilla-foundation/common_voice_13_0"], "metrics": ["wer"]}
transformers safetensors whisper automatic-speech-recognition nl dataset:mozilla-foundation/common_voice_13_0 endpoints_compatible region:us