`NewForSequenceClassification` cannot load for 2 classes classification
#14
by nicozck - opened
Failed for 2 calsses
config = NewConfig.from_pretrained(
r"D:\download_models\gte-multilingual-base",
problem_type="single_label_classification",
label2id={"0": 0, "1": 1 },
id2label={0: "0", 1: "1" },
num_labels=2,
)
model = NewForSequenceClassification.from_pretrained(
r"D:\download_models\gte-multilingual-base",
config=config,
ignore_mismatched_sizes=True,
)
print(model)
Runable for 3 classes
config = NewConfig.from_pretrained(
r"D:\download_models\gte-multilingual-base",
problem_type="single_label_classification",
label2id={"0": 0, "1": 1, "2": 2},
id2label={0: "0", 1: "1", 2: "2"},
num_labels=3,
)
model = NewForSequenceClassification.from_pretrained(
r"D:\download_models\gte-multilingual-base",
config=config,
ignore_mismatched_sizes=True,
)
print(model)
error message:
model = NewForSequenceClassification.from_pretrained(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "\.conda\envs\dev\Lib\site-packages\transformers\modeling_utils.py", line 3960, in from_pretrained
) = cls._load_pretrained_model(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "\.conda\envs\dev\Lib\site-packages\transformers\modeling_utils.py", line 4492, in _load_pretrained_model
raise RuntimeError(f"Error(s) in loading state_dict for {model.__class__.__name__}:\n\t{error_msg}")
RuntimeError: Error(s) in loading state_dict for NewForSequenceClassification:
size mismatch for classifier.bias: copying a param with shape torch.Size([1]) from checkpoint, the shape in current model is torch.Size([2]).
You may consider adding `ignore_mismatched_sizes=True` in the model `from_pretrained` method.