updated run_small.sh to match the end of run1 training

src/run_small.sh

@@ -7,10 +7,10 @@ python src/run_speech_recognition_seq2seq_streaming.py \
 	--eval_split_name="validation" \
 	--model_index_name="Whisper Small Belarusian" \
     \
-	--max_steps="18000" \
+	--max_steps="12000" \
 	--output_dir="./" \
 	--per_device_train_batch_size="64" \
-	--per_device_eval_batch_size="32" \
+	--per_device_eval_batch_size="64" \
 	--logging_steps="50" \
 	--logging_first_step \
 	--learning_rate="1e-4" \
@@ -34,7 +34,6 @@ python src/run_speech_recognition_seq2seq_streaming.py \
     \
 	--do_train \
 	--do_eval \
-	--resume_from_checkpoint="checkpoint-12000" \
 	--ignore_data_skip \
 	--predict_with_generate \
 	--do_normalize_eval \

src/run_speech_recognition_seq2seq_streaming.py

@@ -720,6 +720,7 @@ def main():
             checkpoint = training_args.resume_from_checkpoint
         elif last_checkpoint is not None:
             checkpoint = last_checkpoint
+        logger.info(f'will launch training and pass resume_from_checkpoint={checkpoint}')
         train_result = trainer.train(resume_from_checkpoint=checkpoint)
         trainer.save_model()  # Saves the feature extractor too for easy upload