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ERROR when running train (test method only) #10

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mellahysf opened this issue Mar 12, 2020 · 1 comment
Closed

ERROR when running train (test method only) #10

mellahysf opened this issue Mar 12, 2020 · 1 comment

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@mellahysf
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mellahysf commented Mar 12, 2020 •
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Hi,

Can you help please ??

when i try to run train.py precisaly the test method, it gives me the error below:

BERT-type: uncased_L-24_H-1024_A-16
Batch_size = 32
BERT parameters:
learning rate: 1e-05
Fine-tune BERT: False
vocab size: 30522
hidden_size: 1024
num_hidden_layer: 24
num_attention_heads: 16
hidden_act: gelu
intermediate_size: 4096
hidden_dropout_prob: 0.1
attention_probs_dropout_prob: 0.1
max_position_embeddings: 512
type_vocab_size: 2
initializer_range: 0.02
Load pre-trained parameters.
Seq-to-SQL: the number of final BERT layers to be used: 2
Seq-to-SQL: the size of hidden dimension = 100
Seq-to-SQL: LSTM encoding layer size = 2
Seq-to-SQL: dropout rate = 0.3
Seq-to-SQL: learning rate = 0.001
Traceback (most recent call last):
File "train.py", line 709, in
path_model_bert=path_model_bert, path_model=path_model)
File "train.py", line 187, in get_models
model_bert.load_state_dict(res['model_bert'])
File "/home/ysfmell/.local/lib/python3.6/site-packages/torch/nn/modules/module.py", line 830, in load_state_dict
self.class.name, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for BertModel:
Missing 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, 768]) from checkpoint, the shape in current model is torch.Size([30522, 1024]).
size mismatch for embeddings.position_embeddings.weight: copying a param with shape torch.Size([512, 768]) from checkpoint, the shape in current model is torch.Size([512, 1024]).
size mismatch for embeddings.token_type_embeddings.weight: copying a param with shape torch.Size([2, 768]) from checkpoint, the shape in current model is torch.Size([2, 1024]).
size mismatch for embeddings.LayerNorm.gamma: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for embeddings.LayerNorm.beta: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.0.attention.self.query.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.0.attention.self.query.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.0.attention.self.key.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.0.attention.self.key.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.0.attention.self.value.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.0.attention.self.value.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.0.attention.output.dense.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.0.attention.output.dense.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.0.attention.output.LayerNorm.gamma: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.0.attention.output.LayerNorm.beta: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.0.intermediate.dense.weight: copying a param with shape torch.Size([3072, 768]) from checkpoint, the shape in current model is torch.Size([4096, 1024]).
size mismatch for encoder.layer.0.intermediate.dense.bias: copying a param with shape torch.Size([3072]) from checkpoint, the shape in current model is torch.Size([4096]).
size mismatch for encoder.layer.0.output.dense.weight: copying a param with shape torch.Size([768, 3072]) from checkpoint, the shape in current model is torch.Size([1024, 4096]).
size mismatch for encoder.layer.0.output.dense.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.0.output.LayerNorm.gamma: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.0.output.LayerNorm.beta: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.1.attention.self.query.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.1.attention.self.query.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.1.attention.self.key.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.1.attention.self.key.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.1.attention.self.value.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.1.attention.self.value.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.1.attention.output.dense.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.1.attention.output.dense.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.1.attention.output.LayerNorm.gamma: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.1.attention.output.LayerNorm.beta: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.1.intermediate.dense.weight: copying a param with shape torch.Size([3072, 768]) from checkpoint, the shape in current model is torch.Size([4096, 1024]).
size mismatch for encoder.layer.1.intermediate.dense.bias: copying a param with shape torch.Size([3072]) from checkpoint, the shape in current model is torch.Size([4096]).
size mismatch for encoder.layer.1.output.dense.weight: copying a param with shape torch.Size([768, 3072]) from checkpoint, the shape in current model is torch.Size([1024, 4096]).
size mismatch for encoder.layer.1.output.dense.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.1.output.LayerNorm.gamma: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.1.output.LayerNorm.beta: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.2.attention.self.query.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.2.attention.self.query.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.2.attention.self.key.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.2.attention.self.key.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.2.attention.self.value.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.2.attention.self.value.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.2.attention.output.dense.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.2.attention.output.dense.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.2.attention.output.LayerNorm.gamma: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.2.attention.output.LayerNorm.beta: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.2.intermediate.dense.weight: copying a param with shape torch.Size([3072, 768]) from checkpoint, the shape in current model is torch.Size([4096, 1024]).
size mismatch for encoder.layer.2.intermediate.dense.bias: copying a param with shape torch.Size([3072]) from checkpoint, the shape in current model is torch.Size([4096]).
size mismatch for encoder.layer.2.output.dense.weight: copying a param with shape torch.Size([768, 3072]) from checkpoint, the shape in current model is torch.Size([1024, 4096]).
size mismatch for encoder.layer.2.output.dense.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.2.output.LayerNorm.gamma: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.2.output.LayerNorm.beta: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.3.attention.self.query.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.3.attention.self.query.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.3.attention.self.key.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.3.attention.self.key.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.3.attention.self.value.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.3.attention.self.value.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.3.attention.output.dense.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.3.attention.output.dense.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.3.attention.output.LayerNorm.gamma: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.3.attention.output.LayerNorm.beta: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.3.intermediate.dense.weight: copying a param with shape torch.Size([3072, 768]) from checkpoint, the shape in current model is torch.Size([4096, 1024]).
size mismatch for encoder.layer.3.intermediate.dense.bias: copying a param with shape torch.Size([3072]) from checkpoint, the shape in current model is torch.Size([4096]).
size mismatch for encoder.layer.3.output.dense.weight: copying a param with shape torch.Size([768, 3072]) from checkpoint, the shape in current model is torch.Size([1024, 4096]).
size mismatch for encoder.layer.3.output.dense.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.3.output.LayerNorm.gamma: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.3.output.LayerNorm.beta: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.4.attention.self.query.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.4.attention.self.query.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.4.attention.self.key.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.4.attention.self.key.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.4.attention.self.value.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.4.attention.self.value.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.4.attention.output.dense.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.4.attention.output.dense.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.4.attention.output.LayerNorm.gamma: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.4.attention.output.LayerNorm.beta: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.4.intermediate.dense.weight: copying a param with shape torch.Size([3072, 768]) from checkpoint, the shape in current model is torch.Size([4096, 1024]).
size mismatch for encoder.layer.4.intermediate.dense.bias: copying a param with shape torch.Size([3072]) from checkpoint, the shape in current model is torch.Size([4096]).
size mismatch for encoder.layer.4.output.dense.weight: copying a param with shape torch.Size([768, 3072]) from checkpoint, the shape in current model is torch.Size([1024, 4096]).
size mismatch for encoder.layer.4.output.dense.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.4.output.LayerNorm.gamma: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.4.output.LayerNorm.beta: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.5.attention.self.query.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.5.attention.self.query.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.5.attention.self.key.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.5.attention.self.key.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.5.attention.self.value.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.5.attention.self.value.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.5.attention.output.dense.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.5.attention.output.dense.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.5.attention.output.LayerNorm.gamma: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.5.attention.output.LayerNorm.beta: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.5.intermediate.dense.weight: copying a param with shape torch.Size([3072, 768]) from checkpoint, the shape in current model is torch.Size([4096, 1024]).
size mismatch for encoder.layer.5.intermediate.dense.bias: copying a param with shape torch.Size([3072]) from checkpoint, the shape in current model is torch.Size([4096]).
size mismatch for encoder.layer.5.output.dense.weight: copying a param with shape torch.Size([768, 3072]) from checkpoint, the shape in current model is torch.Size([1024, 4096]).
size mismatch for encoder.layer.5.output.dense.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.5.output.LayerNorm.gamma: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.5.output.LayerNorm.beta: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.6.attention.self.query.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.6.attention.self.query.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.6.attention.self.key.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.6.attention.self.key.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.6.attention.self.value.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.6.attention.self.value.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.6.attention.output.dense.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.6.attention.output.dense.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.6.attention.output.LayerNorm.gamma: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.6.attention.output.LayerNorm.beta: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.6.intermediate.dense.weight: copying a param with shape torch.Size([3072, 768]) from checkpoint, the shape in current model is torch.Size([4096, 1024]).
size mismatch for encoder.layer.6.intermediate.dense.bias: copying a param with shape torch.Size([3072]) from checkpoint, the shape in current model is torch.Size([4096]).
size mismatch for encoder.layer.6.output.dense.weight: copying a param with shape torch.Size([768, 3072]) from checkpoint, the shape in current model is torch.Size([1024, 4096]).
size mismatch for encoder.layer.6.output.dense.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.6.output.LayerNorm.gamma: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.6.output.LayerNorm.beta: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.7.attention.self.query.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.7.attention.self.query.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.7.attention.self.key.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.7.attention.self.key.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.7.attention.self.value.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.7.attention.self.value.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.7.attention.output.dense.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.7.attention.output.dense.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.7.attention.output.LayerNorm.gamma: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.7.attention.output.LayerNorm.beta: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.7.intermediate.dense.weight: copying a param with shape torch.Size([3072, 768]) from checkpoint, the shape in current model is torch.Size([4096, 1024]).
size mismatch for encoder.layer.7.intermediate.dense.bias: copying a param with shape torch.Size([3072]) from checkpoint, the shape in current model is torch.Size([4096]).
size mismatch for encoder.layer.7.output.dense.weight: copying a param with shape torch.Size([768, 3072]) from checkpoint, the shape in current model is torch.Size([1024, 4096]).
size mismatch for encoder.layer.7.output.dense.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.7.output.LayerNorm.gamma: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.7.output.LayerNorm.beta: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.8.attention.self.query.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.8.attention.self.query.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.8.attention.self.key.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.8.attention.self.key.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.8.attention.self.value.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.8.attention.self.value.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.8.attention.output.dense.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.8.attention.output.dense.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.8.attention.output.LayerNorm.gamma: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.8.attention.output.LayerNorm.beta: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.8.intermediate.dense.weight: copying a param with shape torch.Size([3072, 768]) from checkpoint, the shape in current model is torch.Size([4096, 1024]).
size mismatch for encoder.layer.8.intermediate.dense.bias: copying a param with shape torch.Size([3072]) from checkpoint, the shape in current model is torch.Size([4096]).
size mismatch for encoder.layer.8.output.dense.weight: copying a param with shape torch.Size([768, 3072]) from checkpoint, the shape in current model is torch.Size([1024, 4096]).
size mismatch for encoder.layer.8.output.dense.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.8.output.LayerNorm.gamma: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.8.output.LayerNorm.beta: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.9.attention.self.query.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.9.attention.self.query.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.9.attention.self.key.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.9.attention.self.key.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.9.attention.self.value.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.9.attention.self.value.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.9.attention.output.dense.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.9.attention.output.dense.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.9.attention.output.LayerNorm.gamma: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.9.attention.output.LayerNorm.beta: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.9.intermediate.dense.weight: copying a param with shape torch.Size([3072, 768]) from checkpoint, the shape in current model is torch.Size([4096, 1024]).
size mismatch for encoder.layer.9.intermediate.dense.bias: copying a param with shape torch.Size([3072]) from checkpoint, the shape in current model is torch.Size([4096]).
size mismatch for encoder.layer.9.output.dense.weight: copying a param with shape torch.Size([768, 3072]) from checkpoint, the shape in current model is torch.Size([1024, 4096]).
size mismatch for encoder.layer.9.output.dense.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.9.output.LayerNorm.gamma: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.9.output.LayerNorm.beta: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.10.attention.self.query.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.10.attention.self.query.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.10.attention.self.key.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.10.attention.self.key.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.10.attention.self.value.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.10.attention.self.value.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.10.attention.output.dense.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.10.attention.output.dense.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.10.attention.output.LayerNorm.gamma: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.10.attention.output.LayerNorm.beta: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.10.intermediate.dense.weight: copying a param with shape torch.Size([3072, 768]) from checkpoint, the shape in current model is torch.Size([4096, 1024]).
size mismatch for encoder.layer.10.intermediate.dense.bias: copying a param with shape torch.Size([3072]) from checkpoint, the shape in current model is torch.Size([4096]).
size mismatch for encoder.layer.10.output.dense.weight: copying a param with shape torch.Size([768, 3072]) from checkpoint, the shape in current model is torch.Size([1024, 4096]).
size mismatch for encoder.layer.10.output.dense.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.10.output.LayerNorm.gamma: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.10.output.LayerNorm.beta: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.11.attention.self.query.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.11.attention.self.query.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.11.attention.self.key.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.11.attention.self.key.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.11.attention.self.value.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.11.attention.self.value.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.11.attention.output.dense.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for encoder.layer.11.attention.output.dense.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.11.attention.output.LayerNorm.gamma: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.11.attention.output.LayerNorm.beta: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.11.intermediate.dense.weight: copying a param with shape torch.Size([3072, 768]) from checkpoint, the shape in current model is torch.Size([4096, 1024]).
size mismatch for encoder.layer.11.intermediate.dense.bias: copying a param with shape torch.Size([3072]) from checkpoint, the shape in current model is torch.Size([4096]).
size mismatch for encoder.layer.11.output.dense.weight: copying a param with shape torch.Size([768, 3072]) from checkpoint, the shape in current model is torch.Size([1024, 4096]).
size mismatch for encoder.layer.11.output.dense.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.11.output.LayerNorm.gamma: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for encoder.layer.11.output.LayerNorm.beta: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for pooler.dense.weight: copying a param with shape torch.Size([768, 768]) from checkpoint, the shape in current model is torch.Size([1024, 1024]).
size mismatch for pooler.dense.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
@kumarvivek9097
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Hi Mellahysf,
I'm facing the same problem. Did you solve it?
If yes, How?

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@kumarvivek9097 @mellahysf