force train + eval

run_speech_recognition_seq2seq_streaming.py

@@ -346,7 +346,9 @@ def main():
         model_args, data_args, training_args = parser.parse_json_file(json_file=os.path.abspath(sys.argv[1]))
     else:
         model_args, data_args, training_args = parser.parse_args_into_dataclasses()
-
+    training_args.do_train = True
+    training_args.do_eval = True
+    
     # Sending telemetry. Tracking the example usage helps us better allocate resources to maintain them. The
     # information sent is the one passed as arguments along with your Python/PyTorch versions.
     send_example_telemetry("run_speech_recognition_seq2seq_streaming", model_args, data_args)

test_run.sh

@@ -10,8 +10,8 @@ python $1run_speech_recognition_seq2seq_streaming.py \
 	--max_eval_samples="32" \
 	--max_steps="5000" \
 	--output_dir="./" \
-	--per_device_train_batch_size="64" \
-	--per_device_eval_batch_size="32" \
+	--per_device_train_batch_size="8" \
+	--per_device_eval_batch_size="4" \
 	--logging_steps="25" \
 	--learning_rate="1e-5" \
 	--warmup_steps="500" \