Problems with using LongFormer

I am according to the official longformer lot (https://github.com/allenai/longformer) provides methods to use, I use in the code of parts as follows:
`

tokenizer_class = BertTokenizer
model_class = LongformerModel
# directory is fine
pretrained_weights = self.pretrainedBertPath
tokenizer = tokenizer_class.from_pretrained(pretrained_weights)
model = model_class.from_pretrained('longformer-base-4096', gradient_checkpointing=True)
# add_special_tokens will add start and end token
input_ids = torch.tensor([tokenizer.encode(text, add_special_tokens=False)])

`

This warning appeared:
`

Some weights of the model checkpoint at longformer-base-4096 were not used when initializing LongformerModel: ['roberta.embeddings.word_embeddings.weight', 'roberta.embeddings.position_embeddings.weight', 'roberta.embeddings.token_type_embeddings.weight', 'roberta.embeddings.LayerNorm.weight', 'roberta.embeddings.LayerNorm.bias', 'roberta.encoder.layer.0.attention.self.query.weight', 'roberta.encoder.layer.0.attention.self.query.bias', 'roberta.encoder.layer.0.attention.self.key.weight', 'roberta.encoder.layer.0.attention.self.key.bias', 'roberta.encoder.layer.0.attention.self.value.weight', 'roberta.encoder.layer.0.attention.self.value.bias', 'roberta.encoder.layer.0.attention.self.query_global.weight', 'roberta.encoder.layer.0.attention.self.query_global.bias', 'roberta.encoder.layer.0.attention.self.key_global.weight', 'roberta.encoder.layer.0.attention.self.key_global.bias', 'roberta.encoder.layer.0.attention.self.value_global.weight', 'roberta.encoder.layer.0.attention.self.value_global.bias', 'roberta.encoder.layer.0.attention.output.dense.weight', 'roberta.encoder.layer.0.attention.output.dense.bias', 'roberta.encoder.layer.0.attention.output.LayerNorm.weight', 'roberta.encoder.layer.0.attention.output.LayerNorm.bias', 'roberta.encoder.layer.0.intermediate.dense.weight', 'roberta.encoder.layer.0.intermediate.dense.bias', 'roberta.encoder.layer.0.output.dense.weight', 'roberta.encoder.layer.0.output.dense.bias', 'roberta.encoder.layer.0.output.LayerNorm.weight', 'roberta.encoder.layer.0.output.LayerNorm.bias', 'roberta.encoder.layer.1.attention.self.query.weight', 'roberta.encoder.layer.1.attention.self.query.bias', 'roberta.encoder.layer.1.attention.self.key.weight', 'roberta.encoder.layer.1.attention.self.key.bias', 'roberta.encoder.layer.1.attention.self.value.weight', 'roberta.encoder.layer.1.attention.self.value.bias', 'roberta.encoder.layer.1.attention.self.query_global.weight', 'roberta.encoder.layer.1.attention.self.query_global.bias', 'roberta.encoder.layer.1.attention.self.key_global.weight', 'roberta.encoder.layer.1.attention.self.key_global.bias', 'roberta.encoder.layer.1.attention.self.value_global.weight', 'roberta.encoder.layer.1.attention.self.value_global.bias', 'roberta.encoder.layer.1.attention.output.dense.weight', 'roberta.encoder.layer.1.attention.output.dense.bias', 'roberta.encoder.layer.1.attention.output.LayerNorm.weight', 'roberta.encoder.layer.1.attention.output.LayerNorm.bias', 'roberta.encoder.layer.1.intermediate.dense.weight', 'roberta.encoder.layer.1.intermediate.dense.bias', 'roberta.encoder.layer.1.output.dense.weight', 'roberta.encoder.layer.1.output.dense.bias', 'roberta.encoder.layer.1.output.LayerNorm.weight', 'roberta.encoder.layer.1.output.LayerNorm.bias', 'roberta.encoder.layer.2.attention.self.query.weight', 'roberta.encoder.layer.2.attention.self.query.bias', 'roberta.encoder.layer.2.attention.self.key.weight', 'roberta.encoder.layer.2.attention.self.key.bias', 'roberta.encoder.layer.2.attention.self.value.weight', 'roberta.encoder.layer.2.attention.self.value.bias', 'roberta.encoder.layer.2.attention.self.query_global.weight', 'roberta.encoder.layer.2.attention.self.query_global.bias', 'roberta.encoder.layer.2.attention.self.key_global.weight', 'roberta.encoder.layer.2.attention.self.key_global.bias', 'roberta.encoder.layer.2.attention.self.value_global.weight', 'roberta.encoder.layer.2.attention.self.value_global.bias', 'roberta.encoder.layer.2.attention.output.dense.weight', 'roberta.encoder.layer.2.attention.output.dense.bias', 'roberta.encoder.layer.2.attention.output.LayerNorm.weight', 'roberta.encoder.layer.2.attention.output.LayerNorm.bias', 'roberta.encoder.layer.2.intermediate.dense.weight', 'roberta.encoder.layer.2.intermediate.dense.bias', 'roberta.encoder.layer.2.output.dense.weight', 'roberta.encoder.layer.2.output.dense.bias', 'roberta.encoder.layer.2.output.LayerNorm.weight', 'roberta.encoder.layer.2.output.LayerNorm.bias', 'roberta.encoder.layer.3.attention.self.query.weight', 'roberta.encoder.layer.3.attention.self.query.bias', 'roberta.encoder.layer.3.attention.self.key.weight', 'roberta.encoder.layer.3.attention.self.key.bias', 'roberta.encoder.layer.3.attention.self.value.weight', 'roberta.encoder.layer.3.attention.self.value.bias', 'roberta.encoder.layer.3.attention.self.query_global.weight', 'roberta.encoder.layer.3.attention.self.query_global.bias', 'roberta.encoder.layer.3.attention.self.key_global.weight', 'roberta.encoder.layer.3.attention.self.key_global.bias', 'roberta.encoder.layer.3.attention.self.value_global.weight', 'roberta.encoder.layer.3.attention.self.value_global.bias', 'roberta.encoder.layer.3.attention.output.dense.weight', 'roberta.encoder.layer.3.attention.output.dense.bias', 'roberta.encoder.layer.3.attention.output.LayerNorm.weight', 'roberta.encoder.layer.3.attention.output.LayerNorm.bias', 'roberta.encoder.layer.3.intermediate.dense.weight', 'roberta.encoder.layer.3.intermediate.dense.bias', 'roberta.encoder.layer.3.output.dense.weight', 'roberta.encoder.layer.3.output.dense.bias', 'roberta.encoder.layer.3.output.LayerNorm.weight', 'roberta.encoder.layer.3.output.LayerNorm.bias', 'roberta.encoder.layer.4.attention.self.query.weight', 'roberta.encoder.layer.4.attention.self.query.bias', 'roberta.encoder.layer.4.attention.self.key.weight', 'roberta.encoder.layer.4.attention.self.key.bias', 'roberta.encoder.layer.4.attention.self.value.weight', 'roberta.encoder.layer.4.attention.self.value.bias', 'roberta.encoder.layer.4.attention.self.query_global.weight', 'roberta.encoder.layer.4.attention.self.query_global.bias', 'roberta.encoder.layer.4.attention.self.key_global.weight', 'roberta.encoder.layer.4.attention.self.key_global.bias', 'roberta.encoder.layer.4.attention.self.value_global.weight', 'roberta.encoder.layer.4.attention.self.value_global.bias', 'roberta.encoder.layer.4.attention.output.dense.weight', 'roberta.encoder.layer.4.attention.output.dense.bias', 'roberta.encoder.layer.4.attention.output.LayerNorm.weight', 'roberta.encoder.layer.4.attention.output.LayerNorm.bias', 'roberta.encoder.layer.4.intermediate.dense.weight', 'roberta.encoder.layer.4.intermediate.dense.bias', 'roberta.encoder.layer.4.output.dense.weight', 'roberta.encoder.layer.4.output.dense.bias', 'roberta.encoder.layer.4.output.LayerNorm.weight', 'roberta.encoder.layer.4.output.LayerNorm.bias', 'roberta.encoder.layer.5.attention.self.query.weight', 'roberta.encoder.layer.5.attention.self.query.bias', 'roberta.encoder.layer.5.attention.self.key.weight', 'roberta.encoder.layer.5.attention.self.key.bias', 'roberta.encoder.layer.5.attention.self.value.weight', 'roberta.encoder.layer.5.attention.self.value.bias', 'roberta.encoder.layer.5.attention.self.query_global.weight', 'roberta.encoder.layer.5.attention.self.query_global.bias', 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'roberta.encoder.layer.7.attention.self.query.weight', 'roberta.encoder.layer.7.attention.self.query.bias', 'roberta.encoder.layer.7.attention.self.key.weight', 'roberta.encoder.layer.7.attention.self.key.bias', 'roberta.encoder.layer.7.attention.self.value.weight', 'roberta.encoder.layer.7.attention.self.value.bias', 'roberta.encoder.layer.7.attention.self.query_global.weight', 'roberta.encoder.layer.7.attention.self.query_global.bias', 'roberta.encoder.layer.7.attention.self.key_global.weight', 'roberta.encoder.layer.7.attention.self.key_global.bias', 'roberta.encoder.layer.7.attention.self.value_global.weight', 'roberta.encoder.layer.7.attention.self.value_global.bias', 'roberta.encoder.layer.7.attention.output.dense.weight', 'roberta.encoder.layer.7.attention.output.dense.bias', 'roberta.encoder.layer.7.attention.output.LayerNorm.weight', 'roberta.encoder.layer.7.attention.output.LayerNorm.bias', 'roberta.encoder.layer.7.intermediate.dense.weight', 'roberta.encoder.layer.7.intermediate.dense.bias', 'roberta.encoder.layer.7.output.dense.weight', 'roberta.encoder.layer.7.output.dense.bias', 'roberta.encoder.layer.7.output.LayerNorm.weight', 'roberta.encoder.layer.7.output.LayerNorm.bias', 'roberta.encoder.layer.8.attention.self.query.weight', 'roberta.encoder.layer.8.attention.self.query.bias', 'roberta.encoder.layer.8.attention.self.key.weight', 'roberta.encoder.layer.8.attention.self.key.bias', 'roberta.encoder.layer.8.attention.self.value.weight', 'roberta.encoder.layer.8.attention.self.value.bias', 'roberta.encoder.layer.8.attention.self.query_global.weight', 'roberta.encoder.layer.8.attention.self.query_global.bias', 'roberta.encoder.layer.8.attention.self.key_global.weight', 'roberta.encoder.layer.8.attention.self.key_global.bias', 'roberta.encoder.layer.8.attention.self.value_global.weight', 'roberta.encoder.layer.8.attention.self.value_global.bias', 'roberta.encoder.layer.8.attention.output.dense.weight', 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'roberta.encoder.layer.10.attention.self.value.bias', 'roberta.encoder.layer.10.attention.self.query_global.weight', 'roberta.encoder.layer.10.attention.self.query_global.bias', 'roberta.encoder.layer.10.attention.self.key_global.weight', 'roberta.encoder.layer.10.attention.self.key_global.bias', 'roberta.encoder.layer.10.attention.self.value_global.weight', 'roberta.encoder.layer.10.attention.self.value_global.bias', 'roberta.encoder.layer.10.attention.output.dense.weight', 'roberta.encoder.layer.10.attention.output.dense.bias', 'roberta.encoder.layer.10.attention.output.LayerNorm.weight', 'roberta.encoder.layer.10.attention.output.LayerNorm.bias', 'roberta.encoder.layer.10.intermediate.dense.weight', 'roberta.encoder.layer.10.intermediate.dense.bias', 'roberta.encoder.layer.10.output.dense.weight', 'roberta.encoder.layer.10.output.dense.bias', 'roberta.encoder.layer.10.output.LayerNorm.weight', 'roberta.encoder.layer.10.output.LayerNorm.bias', 'roberta.encoder.layer.11.attention.self.query.weight', 'roberta.encoder.layer.11.attention.self.query.bias', 'roberta.encoder.layer.11.attention.self.key.weight', 'roberta.encoder.layer.11.attention.self.key.bias', 'roberta.encoder.layer.11.attention.self.value.weight', 'roberta.encoder.layer.11.attention.self.value.bias', 'roberta.encoder.layer.11.attention.self.query_global.weight', 'roberta.encoder.layer.11.attention.self.query_global.bias', 'roberta.encoder.layer.11.attention.self.key_global.weight', 'roberta.encoder.layer.11.attention.self.key_global.bias', 'roberta.encoder.layer.11.attention.self.value_global.weight', 'roberta.encoder.layer.11.attention.self.value_global.bias', 'roberta.encoder.layer.11.attention.output.dense.weight', 'roberta.encoder.layer.11.attention.output.dense.bias', 'roberta.encoder.layer.11.attention.output.LayerNorm.weight', 'roberta.encoder.layer.11.attention.output.LayerNorm.bias', 'roberta.encoder.layer.11.intermediate.dense.weight', 'roberta.encoder.layer.11.intermediate.dense.bias', 'roberta.encoder.layer.11.output.dense.weight', 'roberta.encoder.layer.11.output.dense.bias', 'roberta.encoder.layer.11.output.LayerNorm.weight', 'roberta.encoder.layer.11.output.LayerNorm.bias', 'roberta.pooler.dense.weight', 'roberta.pooler.dense.bias', 'lm_head.bias', 'lm_head.dense.weight', 'lm_head.dense.bias', 'lm_head.layer_norm.weight', 'lm_head.layer_norm.bias', 'lm_head.decoder.weight']
- This IS expected if you are initializing LongformerModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing LongformerModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
Some weights of LongformerModel were not initialized from the model checkpoint at longformer-base-4096 and are newly initialized: ['embeddings.word_embeddings.weight', 'embeddings.position_embeddings.weight', 'embeddings.token_type_embeddings.weight', 'embeddings.LayerNorm.weight', 'embeddings.LayerNorm.bias', 'encoder.layer.0.attention.self.query.weight', 'encoder.layer.0.attention.self.query.bias', 'encoder.layer.0.attention.self.key.weight', 'encoder.layer.0.attention.self.key.bias', 'encoder.layer.0.attention.self.value.weight', 'encoder.layer.0.attention.self.value.bias', 'encoder.layer.0.attention.self.query_global.weight', 'encoder.layer.0.attention.self.query_global.bias', 'encoder.layer.0.attention.self.key_global.weight', 'encoder.layer.0.attention.self.key_global.bias', 'encoder.layer.0.attention.self.value_global.weight', 'encoder.layer.0.attention.self.value_global.bias', 'encoder.layer.0.attention.output.dense.weight', 'encoder.layer.0.attention.output.dense.bias', 'encoder.layer.0.attention.output.LayerNorm.weight', 'encoder.layer.0.attention.output.LayerNorm.bias', 'encoder.layer.0.intermediate.dense.weight', 'encoder.layer.0.intermediate.dense.bias', 'encoder.layer.0.output.dense.weight', 'encoder.layer.0.output.dense.bias', 'encoder.layer.0.output.LayerNorm.weight', 'encoder.layer.0.output.LayerNorm.bias', 'encoder.layer.1.attention.self.query.weight', 'encoder.layer.1.attention.self.query.bias', 'encoder.layer.1.attention.self.key.weight', 'encoder.layer.1.attention.self.key.bias', 'encoder.layer.1.attention.self.value.weight', 'encoder.layer.1.attention.self.value.bias', 'encoder.layer.1.attention.self.query_global.weight', 'encoder.layer.1.attention.self.query_global.bias', 'encoder.layer.1.attention.self.key_global.weight', 'encoder.layer.1.attention.self.key_global.bias', 'encoder.layer.1.attention.self.value_global.weight', 'encoder.layer.1.attention.self.value_global.bias', 'encoder.layer.1.attention.output.dense.weight', 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'pooler.dense.bias'] You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.

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I would like to ask whether the presence of this warning will affect the results?How can remove this warning?thinks