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Comments (7)

techwithshadab avatar techwithshadab commented on August 28, 2024 2

Hi @todpole3

I found huggingface team has changed the variables names in their "updated" code.

https://github.com/huggingface/pytorch-pretrained-BERT/blob/c35d9d48d91282f7b7776751fc5630b1af1d3b97/pytorch_pretrained_bert/modeling.py#L220-L233

Previously, self.weight in BERTLayerNorm was self.gamma and self.bias was self.beta.

See below.

sqlova/bert/modeling.py

Lines 131 to 138 in b7ce9ad

class BERTLayerNorm(nn.Module):
def __init__(self, config, variance_epsilon=1e-12):
"""Construct a layernorm module in the TF style (epsilon inside the square root).
"""
super(BERTLayerNorm, self).__init__()
self.gamma = nn.Parameter(torch.ones(config.hidden_size))
self.beta = nn.Parameter(torch.zeros(config.hidden_size))
self.variance_epsilon = variance_epsilon

For the compatibility, please use the old convert_tf_checkpoint_to_pytorch.py which I have used.

Thanks!

Wonseok

Can we update those changes in this repo also?

from sqlova.

whwang299 avatar whwang299 commented on August 28, 2024 1

Hi @todpole3

I found huggingface team has changed the variables names in their "updated" code.

https://github.com/huggingface/pytorch-pretrained-BERT/blob/c35d9d48d91282f7b7776751fc5630b1af1d3b97/pytorch_pretrained_bert/modeling.py#L220-L233

Previously, self.weight in BERTLayerNorm was self.gamma and self.bias was self.beta.

See below.

sqlova/bert/modeling.py

Lines 131 to 138 in b7ce9ad

class BERTLayerNorm(nn.Module):
def __init__(self, config, variance_epsilon=1e-12):
"""Construct a layernorm module in the TF style (epsilon inside the square root).
"""
super(BERTLayerNorm, self).__init__()
self.gamma = nn.Parameter(torch.ones(config.hidden_size))
self.beta = nn.Parameter(torch.zeros(config.hidden_size))
self.variance_epsilon = variance_epsilon

For the compatibility, please use the old convert_tf_checkpoint_to_pytorch.py which I have used.

Thanks!

Wonseok

from sqlova.

todpole3 avatar todpole3 commented on August 28, 2024

That makes a lot of sense. Thanks for the quick response!

from sqlova.

luckysunda avatar luckysunda commented on August 28, 2024

I am using everyhing from the repo itself but still getting this error:

RuntimeError: Error(s) in loading state_dict for BertModel:
	Unexpected key(s) in state_dict: "encoder.layer.12.attention.self.query.weight", "encoder.layer.12.attention.self.query.bias", "encoder.layer.12.attention.self.key.weight", "encoder.layer.12.attention.self.key.bias", "encoder.layer.12.attention.self.value.weight", "encoder.layer.12.attention.self.value.bias", "encoder.layer.12.attention.output.dense.weight", "encoder.layer.12.attention.output.dense.bias", "encoder.layer.12.attention.output.LayerNorm.gamma", "encoder.layer.12.attention.output.LayerNorm.beta", "encoder.layer.12.intermediate.dense.weight", "encoder.layer.12.intermediate.dense.bias", "encoder.layer.12.output.dense.weight", "encoder.layer.12.output.dense.bias", "encoder.layer.12.output.LayerNorm.gamma", "encoder.layer.12.output.LayerNorm.beta", "encoder.layer.13.attention.self.query.weight", "encoder.layer.13.attention.self.query.bias", "encoder.layer.13.attention.self.key.weight", "encoder.layer.13.attention.self.key.bias", "encoder.layer.13.attention.self.value.weight", "encoder.layer.13.attention.self.value.bias", "encoder.layer.13.attention.output.dense.weight", "encoder.layer.13.attention.output.dense.bias", "encoder.layer.13.attention.output.LayerNorm.gamma", "encoder.layer.13.attention.output.LayerNorm.beta", "encoder.layer.13.intermediate.dense.weight", "encoder.layer.13.intermediate.dense.bias", "encoder.layer.13.output.dense.weight", "encoder.layer.13.output.dense.bias", "encoder.layer.13.output.LayerNorm.gamma", "encoder.layer.13.output.LayerNorm.beta", "encoder.layer.14.attention.self.query.weight", "encoder.layer.14.attention.self.query.bias", "encoder.layer.14.attention.self.key.weight", "encoder.layer.14.attention.self.key.bias", "encoder.layer.14.attention.self.value.weight", "encoder.layer.14.attention.self.value.bias", "encoder.layer.14.attention.output.dense.weight", "encoder.layer.14.attention.output.dense.bias", "encoder.layer.14.attention.output.LayerNorm.gamma", "encoder.layer.14.attention.output.LayerNorm.beta", "encoder.layer.14.intermediate.dense.weight", "encoder.layer.14.intermediate.dense.bias", "encoder.layer.14.output.dense.weight", "encoder.layer.14.output.dense.bias", "encoder.layer.14.output.LayerNorm.gamma", "encoder.layer.14.output.LayerNorm.beta", "encoder.layer.15.attention.self.query.weight", "encoder.layer.15.attention.self.query.bias", "encoder.layer.15.attention.self.key.weight", "encoder.layer.15.attention.self.key.bias", "encoder.layer.15.attention.self.value.weight", "encoder.layer.15.attention.self.value.bias", "encoder.layer.15.attention.output.dense.weight", "encoder.layer.15.attention.output.dense.bias", "encoder.layer.15.attention.output.LayerNorm.gamma", "encoder.layer.15.attention.output.LayerNorm.beta", "encoder.layer.15.intermediate.dense.weight", "encoder.layer.15.intermediate.dense.bias", "encoder.layer.15.output.dense.weight", "encoder.layer.15.output.dense.bias", "encoder.layer.15.output.LayerNorm.gamma", "encoder.layer.15.output.LayerNorm.beta", "encoder.layer.16.attention.self.query.weight", "encoder.layer.16.attention.self.query.bias", "encoder.layer.16.attention.self.key.weight", "encoder.layer.16.attention.self.key.bias", "encoder.layer.16.attention.self.value.weight", "encoder.layer.16.attention.self.value.bias", "encoder.layer.16.attention.output.dense.weight", "encoder.layer.16.attention.output.dense.bias", "encoder.layer.16.attention.output.LayerNorm.gamma", "encoder.layer.16.attention.output.LayerNorm.beta", "encoder.layer.16.intermediate.dense.weight", "encoder.layer.16.intermediate.dense.bias", "encoder.layer.16.output.dense.weight", "encoder.layer.16.output.dense.bias", "encoder.layer.16.output.LayerNorm.gamma", "encoder.layer.16.output.LayerNorm.beta", "encoder.layer.17.attention.self.query.weight", "encoder.layer.17.attention.self.query.bias", "encoder.layer.17.attention.self.key.weight", "encoder.layer.17.attention.self.key.bias", "encoder.layer.17.attention.self.value.weight", "encoder.layer.17.attention.self.value.bias", "encoder.layer.17.attention.output.dense.weight", "encoder.layer.17.attention.output.dense.bias", "encoder.layer.17.attention.output.LayerNorm.gamma", "encoder.layer.17.attention.output.LayerNorm.beta", "encoder.layer.17.intermediate.dense.weight", "encoder.layer.17.intermediate.dense.bias", "encoder.layer.17.output.dense.weight", "encoder.layer.17.output.dense.bias", "encoder.layer.17.output.LayerNorm.gamma", "encoder.layer.17.output.LayerNorm.beta", "encoder.layer.18.attention.self.query.weight", "encoder.layer.18.attention.self.query.bias", "encoder.layer.18.attention.self.key.weight", "encoder.layer.18.attention.self.key.bias", "encoder.layer.18.attention.self.value.weight", "encoder.layer.18.attention.self.value.bias", "encoder.layer.18.attention.output.dense.weight", "encoder.layer.18.attention.output.dense.bias", "encoder.layer.18.attention.output.LayerNorm.gamma", "encoder.layer.18.attention.output.LayerNorm.beta", "encoder.layer.18.intermediate.dense.weight", "encoder.layer.18.intermediate.dense.bias", "encoder.layer.18.output.dense.weight", "encoder.layer.18.output.dense.bias", "encoder.layer.18.output.LayerNorm.gamma", "encoder.layer.18.output.LayerNorm.beta", "encoder.layer.19.attention.self.query.weight", "encoder.layer.19.attention.self.query.bias", "encoder.layer.19.attention.self.key.weight", "encoder.layer.19.attention.self.key.bias", "encoder.layer.19.attention.self.value.weight", "encoder.layer.19.attention.self.value.bias", "encoder.layer.19.attention.output.dense.weight", "encoder.layer.19.attention.output.dense.bias", "encoder.layer.19.attention.output.LayerNorm.gamma", "encoder.layer.19.attention.output.LayerNorm.beta", "encoder.layer.19.intermediate.dense.weight", "encoder.layer.19.intermediate.dense.bias", "encoder.layer.19.output.dense.weight", "encoder.layer.19.output.dense.bias", "encoder.layer.19.output.LayerNorm.gamma", "encoder.layer.19.output.LayerNorm.beta", "encoder.layer.20.attention.self.query.weight", "encoder.layer.20.attention.self.query.bias", "encoder.layer.20.attention.self.key.weight", "encoder.layer.20.attention.self.key.bias", "encoder.layer.20.attention.self.value.weight", "encoder.layer.20.attention.self.value.bias", "encoder.layer.20.attention.output.dense.weight", "encoder.layer.20.attention.output.dense.bias", "encoder.layer.20.attention.output.LayerNorm.gamma", "encoder.layer.20.attention.output.LayerNorm.beta", "encoder.layer.20.intermediate.dense.weight", "encoder.layer.20.intermediate.dense.bias", "encoder.layer.20.output.dense.weight", "encoder.layer.20.output.dense.bias", "encoder.layer.20.output.LayerNorm.gamma", "encoder.layer.20.output.LayerNorm.beta", "encoder.layer.21.attention.self.query.weight", "encoder.layer.21.attention.self.query.bias", "encoder.layer.21.attention.self.key.weight", "encoder.layer.21.attention.self.key.bias", "encoder.layer.21.attention.self.value.weight", "encoder.layer.21.attention.self.value.bias", "encoder.layer.21.attention.output.dense.weight", "encoder.layer.21.attention.output.dense.bias", "encoder.layer.21.attention.output.LayerNorm.gamma", "encoder.layer.21.attention.output.LayerNorm.beta", "encoder.layer.21.intermediate.dense.weight", "encoder.layer.21.intermediate.dense.bias", "encoder.layer.21.output.dense.weight", "encoder.layer.21.output.dense.bias", "encoder.layer.21.output.LayerNorm.gamma", "encoder.layer.21.output.LayerNorm.beta", "encoder.layer.22.attention.self.query.weight", "encoder.layer.22.attention.self.query.bias", "encoder.layer.22.attention.self.key.weight", "encoder.layer.22.attention.self.key.bias", "encoder.layer.22.attention.self.value.weight", "encoder.layer.22.attention.self.value.bias", "encoder.layer.22.attention.output.dense.weight", "encoder.layer.22.attention.output.dense.bias", "encoder.layer.22.attention.output.LayerNorm.gamma", "encoder.layer.22.attention.output.LayerNorm.beta", "encoder.layer.22.intermediate.dense.weight", "encoder.layer.22.intermediate.dense.bias", "encoder.layer.22.output.dense.weight", "encoder.layer.22.output.dense.bias", "encoder.layer.22.output.LayerNorm.gamma", "encoder.layer.22.output.LayerNorm.beta", "encoder.layer.23.attention.self.query.weight", "encoder.layer.23.attention.self.query.bias", "encoder.layer.23.attention.self.key.weight", "encoder.layer.23.attention.self.key.bias", "encoder.layer.23.attention.self.value.weight", "encoder.layer.23.attention.self.value.bias", "encoder.layer.23.attention.output.dense.weight", "encoder.layer.23.attention.output.dense.bias", "encoder.layer.23.attention.output.LayerNorm.gamma", "encoder.layer.23.attention.output.LayerNorm.beta", "encoder.layer.23.intermediate.dense.weight", "encoder.layer.23.intermediate.dense.bias", "encoder.layer.23.output.dense.weight", "encoder.layer.23.output.dense.bias", "encoder.layer.23.output.LayerNorm.gamma", "encoder.layer.23.output.LayerNorm.beta". 
	size mismatch for embeddings.word_embeddings.weight: copying a param with shape torch.Size([30522, 1024]) from checkpoint, the shape in current model is torch.Size([30522, 768]).
	size mismatch for embeddings.position_embeddings.weight: copying a param with shape torch.Size([512, 1024]) from checkpoint, the shape in current model is torch.Size([512, 768]).
	size mismatch for embeddings.token_type_embeddings.weight: copying a param with shape torch.Size([2, 1024]) from checkpoint, the shape in current model is torch.Size([2, 768]).
	size mismatch for embeddings.LayerNorm.gamma: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for embeddings.LayerNorm.beta: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.0.attention.self.query.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.0.attention.self.query.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.0.attention.self.key.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.0.attention.self.key.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.0.attention.self.value.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.0.attention.self.value.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.0.attention.output.dense.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.0.attention.output.dense.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.0.attention.output.LayerNorm.gamma: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.0.attention.output.LayerNorm.beta: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.0.intermediate.dense.weight: copying a param with shape torch.Size([4096, 1024]) from checkpoint, the shape in current model is torch.Size([3072, 768]).
	size mismatch for encoder.layer.0.intermediate.dense.bias: copying a param with shape torch.Size([4096]) from checkpoint, the shape in current model is torch.Size([3072]).
	size mismatch for encoder.layer.0.output.dense.weight: copying a param with shape torch.Size([1024, 4096]) from checkpoint, the shape in current model is torch.Size([768, 3072]).
	size mismatch for encoder.layer.0.output.dense.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.0.output.LayerNorm.gamma: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.0.output.LayerNorm.beta: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.1.attention.self.query.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.1.attention.self.query.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.1.attention.self.key.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.1.attention.self.key.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.1.attention.self.value.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.1.attention.self.value.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.1.attention.output.dense.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.1.attention.output.dense.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.1.attention.output.LayerNorm.gamma: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.1.attention.output.LayerNorm.beta: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.1.intermediate.dense.weight: copying a param with shape torch.Size([4096, 1024]) from checkpoint, the shape in current model is torch.Size([3072, 768]).
	size mismatch for encoder.layer.1.intermediate.dense.bias: copying a param with shape torch.Size([4096]) from checkpoint, the shape in current model is torch.Size([3072]).
	size mismatch for encoder.layer.1.output.dense.weight: copying a param with shape torch.Size([1024, 4096]) from checkpoint, the shape in current model is torch.Size([768, 3072]).
	size mismatch for encoder.layer.1.output.dense.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.1.output.LayerNorm.gamma: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.1.output.LayerNorm.beta: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.2.attention.self.query.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.2.attention.self.query.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.2.attention.self.key.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.2.attention.self.key.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.2.attention.self.value.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.2.attention.self.value.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.2.attention.output.dense.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.2.attention.output.dense.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.2.attention.output.LayerNorm.gamma: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.2.attention.output.LayerNorm.beta: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.2.intermediate.dense.weight: copying a param with shape torch.Size([4096, 1024]) from checkpoint, the shape in current model is torch.Size([3072, 768]).
	size mismatch for encoder.layer.2.intermediate.dense.bias: copying a param with shape torch.Size([4096]) from checkpoint, the shape in current model is torch.Size([3072]).
	size mismatch for encoder.layer.2.output.dense.weight: copying a param with shape torch.Size([1024, 4096]) from checkpoint, the shape in current model is torch.Size([768, 3072]).
	size mismatch for encoder.layer.2.output.dense.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.2.output.LayerNorm.gamma: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.2.output.LayerNorm.beta: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.3.attention.self.query.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.3.attention.self.query.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.3.attention.self.key.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.3.attention.self.key.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.3.attention.self.value.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.3.attention.self.value.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.3.attention.output.dense.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.3.attention.output.dense.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.3.attention.output.LayerNorm.gamma: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.3.attention.output.LayerNorm.beta: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.3.intermediate.dense.weight: copying a param with shape torch.Size([4096, 1024]) from checkpoint, the shape in current model is torch.Size([3072, 768]).
	size mismatch for encoder.layer.3.intermediate.dense.bias: copying a param with shape torch.Size([4096]) from checkpoint, the shape in current model is torch.Size([3072]).
	size mismatch for encoder.layer.3.output.dense.weight: copying a param with shape torch.Size([1024, 4096]) from checkpoint, the shape in current model is torch.Size([768, 3072]).
	size mismatch for encoder.layer.3.output.dense.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.3.output.LayerNorm.gamma: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.3.output.LayerNorm.beta: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.4.attention.self.query.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.4.attention.self.query.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.4.attention.self.key.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.4.attention.self.key.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.4.attention.self.value.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.4.attention.self.value.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.4.attention.output.dense.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.4.attention.output.dense.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.4.attention.output.LayerNorm.gamma: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.4.attention.output.LayerNorm.beta: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.4.intermediate.dense.weight: copying a param with shape torch.Size([4096, 1024]) from checkpoint, the shape in current model is torch.Size([3072, 768]).
	size mismatch for encoder.layer.4.intermediate.dense.bias: copying a param with shape torch.Size([4096]) from checkpoint, the shape in current model is torch.Size([3072]).
	size mismatch for encoder.layer.4.output.dense.weight: copying a param with shape torch.Size([1024, 4096]) from checkpoint, the shape in current model is torch.Size([768, 3072]).
	size mismatch for encoder.layer.4.output.dense.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.4.output.LayerNorm.gamma: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.4.output.LayerNorm.beta: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.5.attention.self.query.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.5.attention.self.query.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.5.attention.self.key.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.5.attention.self.key.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.5.attention.self.value.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.5.attention.self.value.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.5.attention.output.dense.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.5.attention.output.dense.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.5.attention.output.LayerNorm.gamma: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.5.attention.output.LayerNorm.beta: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.5.intermediate.dense.weight: copying a param with shape torch.Size([4096, 1024]) from checkpoint, the shape in current model is torch.Size([3072, 768]).
	size mismatch for encoder.layer.5.intermediate.dense.bias: copying a param with shape torch.Size([4096]) from checkpoint, the shape in current model is torch.Size([3072]).
	size mismatch for encoder.layer.5.output.dense.weight: copying a param with shape torch.Size([1024, 4096]) from checkpoint, the shape in current model is torch.Size([768, 3072]).
	size mismatch for encoder.layer.5.output.dense.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.5.output.LayerNorm.gamma: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.5.output.LayerNorm.beta: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.6.attention.self.query.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.6.attention.self.query.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.6.attention.self.key.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.6.attention.self.key.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.6.attention.self.value.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.6.attention.self.value.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.6.attention.output.dense.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.6.attention.output.dense.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.6.attention.output.LayerNorm.gamma: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.6.attention.output.LayerNorm.beta: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.6.intermediate.dense.weight: copying a param with shape torch.Size([4096, 1024]) from checkpoint, the shape in current model is torch.Size([3072, 768]).
	size mismatch for encoder.layer.6.intermediate.dense.bias: copying a param with shape torch.Size([4096]) from checkpoint, the shape in current model is torch.Size([3072]).
	size mismatch for encoder.layer.6.output.dense.weight: copying a param with shape torch.Size([1024, 4096]) from checkpoint, the shape in current model is torch.Size([768, 3072]).
	size mismatch for encoder.layer.6.output.dense.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.6.output.LayerNorm.gamma: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.6.output.LayerNorm.beta: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.7.attention.self.query.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.7.attention.self.query.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.7.attention.self.key.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.7.attention.self.key.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.7.attention.self.value.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.7.attention.self.value.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.7.attention.output.dense.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.7.attention.output.dense.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.7.attention.output.LayerNorm.gamma: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.7.attention.output.LayerNorm.beta: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.7.intermediate.dense.weight: copying a param with shape torch.Size([4096, 1024]) from checkpoint, the shape in current model is torch.Size([3072, 768]).
	size mismatch for encoder.layer.7.intermediate.dense.bias: copying a param with shape torch.Size([4096]) from checkpoint, the shape in current model is torch.Size([3072]).
	size mismatch for encoder.layer.7.output.dense.weight: copying a param with shape torch.Size([1024, 4096]) from checkpoint, the shape in current model is torch.Size([768, 3072]).
	size mismatch for encoder.layer.7.output.dense.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.7.output.LayerNorm.gamma: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.7.output.LayerNorm.beta: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.8.attention.self.query.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.8.attention.self.query.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.8.attention.self.key.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.8.attention.self.key.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.8.attention.self.value.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.8.attention.self.value.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.8.attention.output.dense.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.8.attention.output.dense.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.8.attention.output.LayerNorm.gamma: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.8.attention.output.LayerNorm.beta: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.8.intermediate.dense.weight: copying a param with shape torch.Size([4096, 1024]) from checkpoint, the shape in current model is torch.Size([3072, 768]).
	size mismatch for encoder.layer.8.intermediate.dense.bias: copying a param with shape torch.Size([4096]) from checkpoint, the shape in current model is torch.Size([3072]).
	size mismatch for encoder.layer.8.output.dense.weight: copying a param with shape torch.Size([1024, 4096]) from checkpoint, the shape in current model is torch.Size([768, 3072]).
	size mismatch for encoder.layer.8.output.dense.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.8.output.LayerNorm.gamma: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.8.output.LayerNorm.beta: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.9.attention.self.query.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.9.attention.self.query.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.9.attention.self.key.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.9.attention.self.key.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.9.attention.self.value.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.9.attention.self.value.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.9.attention.output.dense.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.9.attention.output.dense.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.9.attention.output.LayerNorm.gamma: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.9.attention.output.LayerNorm.beta: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.9.intermediate.dense.weight: copying a param with shape torch.Size([4096, 1024]) from checkpoint, the shape in current model is torch.Size([3072, 768]).
	size mismatch for encoder.layer.9.intermediate.dense.bias: copying a param with shape torch.Size([4096]) from checkpoint, the shape in current model is torch.Size([3072]).
	size mismatch for encoder.layer.9.output.dense.weight: copying a param with shape torch.Size([1024, 4096]) from checkpoint, the shape in current model is torch.Size([768, 3072]).
	size mismatch for encoder.layer.9.output.dense.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.9.output.LayerNorm.gamma: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.9.output.LayerNorm.beta: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.10.attention.self.query.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.10.attention.self.query.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.10.attention.self.key.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.10.attention.self.key.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.10.attention.self.value.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.10.attention.self.value.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.10.attention.output.dense.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.10.attention.output.dense.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.10.attention.output.LayerNorm.gamma: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.10.attention.output.LayerNorm.beta: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.10.intermediate.dense.weight: copying a param with shape torch.Size([4096, 1024]) from checkpoint, the shape in current model is torch.Size([3072, 768]).
	size mismatch for encoder.layer.10.intermediate.dense.bias: copying a param with shape torch.Size([4096]) from checkpoint, the shape in current model is torch.Size([3072]).
	size mismatch for encoder.layer.10.output.dense.weight: copying a param with shape torch.Size([1024, 4096]) from checkpoint, the shape in current model is torch.Size([768, 3072]).
	size mismatch for encoder.layer.10.output.dense.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.10.output.LayerNorm.gamma: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.10.output.LayerNorm.beta: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.11.attention.self.query.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.11.attention.self.query.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.11.attention.self.key.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.11.attention.self.key.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.11.attention.self.value.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.11.attention.self.value.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.11.attention.output.dense.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for encoder.layer.11.attention.output.dense.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.11.attention.output.LayerNorm.gamma: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.11.attention.output.LayerNorm.beta: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.11.intermediate.dense.weight: copying a param with shape torch.Size([4096, 1024]) from checkpoint, the shape in current model is torch.Size([3072, 768]).
	size mismatch for encoder.layer.11.intermediate.dense.bias: copying a param with shape torch.Size([4096]) from checkpoint, the shape in current model is torch.Size([3072]).
	size mismatch for encoder.layer.11.output.dense.weight: copying a param with shape torch.Size([1024, 4096]) from checkpoint, the shape in current model is torch.Size([768, 3072]).
	size mismatch for encoder.layer.11.output.dense.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.11.output.LayerNorm.gamma: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for encoder.layer.11.output.LayerNorm.beta: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).
	size mismatch for pooler.dense.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([768, 768]).
	size mismatch for pooler.dense.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([768]).

What can be done?

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luckysunda avatar luckysunda commented on August 28, 2024

It got solved, I used different bert model.

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techwithshadab avatar techwithshadab commented on August 28, 2024

It got solved, I used different bert model.

Can you share that model? Even I'm facing the same issue

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Adherer avatar Adherer commented on August 28, 2024

mark

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Related Issues (20)

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