Closed ayush714 closed 2 years ago
I am getting this error, by using below code:-
ValueError: Configurable 'make_layer_stack' doesn't have a parameter named 'use_universal_transformer'. In file "gs://unifiedqa/models/large/operative_config.gin", line 83 decoder/make_layer_stack.use_universal_transformer = False MODEL_SIZE = "large" BASE_PRETRAINED_DIR = "gs://unifiedqa/models/large" PRETRAINED_DIR = BASE_PRETRAINED_DIR MODEL_DIR = os.path.join(MODEL_DIR, MODEL_SIZE)
model_parallelism, train_batch_size, keep_checkpoint_max = { "small": (1, 256, 16), "base": (2, 128, 8), "large": (8, 64, 4), "3B": (8, 16, 1), "11B": (8, 16, 1)}[MODEL_SIZE] tf.io.gfile.makedirs(MODEL_DIR) ON_CLOUD = False model = t5.models.MtfModel( model_dir=MODEL_DIR, tpu=None, model_parallelism=model_parallelism, batch_size=train_batch_size, sequence_length={"inputs": 128, "targets": 32}, learning_rate_schedule=0.003, save_checkpoints_steps=5000, keep_checkpoint_max=keep_checkpoint_max if ON_CLOUD else None, iterations_per_loop=100, ) FINETUNE_STEPS = 9 logInfo("Started Training the model") start = time() model.finetune( mixture_or_task_name="qa_t5_meshs", pretrained_model_dir=PRETRAINED_DIR, finetune_steps=FINETUNE_STEPS ) logInfo("Completed model training.", time_taken=time() - start) ```How I can fix this? I have seen one answer in issues, but I don't know what you're trying to say.
https://github.com/google-research/text-to-text-transfer-transformer/issues/180
@danyaljj I have seen this so when I use 0.1.12 it give me another errors, and it is not resolving the issue!
I tried with most of the versions but still getting the same error!
I am getting this error, by using below code:-