Comments (7)
Hi @todpole3
I found huggingface team has changed the variables names in their "updated" code.
Previously,
self.weight
in BERTLayerNorm wasself.gamma
andself.bias
wasself.beta
.See below.
Lines 131 to 138 in b7ce9ad
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.
Hi @todpole3
I found huggingface team has changed the variables names in their "updated" code.
Previously, self.weight
in BERTLayerNorm was self.gamma
and self.bias
was self.beta
.
See below.
Lines 131 to 138 in b7ce9ad
For the compatibility, please use the old convert_tf_checkpoint_to_pytorch.py
which I have used.
Thanks!
Wonseok
from sqlova.
That makes a lot of sense. Thanks for the quick response!
from sqlova.
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?
from sqlova.
It got solved, I used different bert model.
from sqlova.
It got solved, I used different bert model.
Can you share that model? Even I'm facing the same issue
from sqlova.
mark
from sqlova.
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