Shape mismatch warning

[TuTruongVian]

I trained T5 Base from scratch with different dataset (Wikipedia). Use the checkpoint #60,000 to fine tune for other downstream task (a Seq2Seq task). However, when I load the model from local folder with command : model = T5ForConditionalGeneration.from_pretrained(model_name_or_path, local_files_only=True ), I got the warning message below. Questions: is that normal? Does this affect the performance of final finetuned model?
WARNING:
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
Some weights of the model checkpoint at /home/.../checkpoint-pt-60001/ were not used when initializing T5ForConditionalGeneration: ['encoder.block.8.layer.1.DenseReluDense.wi_1.weight', 'decoder.block.1.layer.2.DenseReluDense.wi_1.weight', 'decoder.block.5.layer.2.DenseReluDense.wi_1.weight', 'encoder.block.5.layer.1.DenseReluDense.wi_0.weight', 'decoder.block.3.layer.2.DenseReluDense.wi_0.weight', 'decoder.block.2.layer.2.DenseReluDense.wi_1.weight', 'encoder.block.11.layer.1.DenseReluDense.wi_1.weight', 'decoder.block.0.layer.2.DenseReluDense.wi_1.weight', 'decoder.block.7.layer.2.DenseReluDense.wi_0.weight', 'decoder.block.11.layer.2.DenseReluDense.wi_1.weight', 'decoder.block.4.layer.2.DenseReluDense.wi_0.weight', 'encoder.block.1.layer.1.DenseReluDense.wi_0.weight', 'encoder.block.7.layer.1.DenseReluDense.wi_1.weight', 'encoder.block.7.layer.1.DenseReluDense.wi_0.weight', 'encoder.block.5.layer.1.DenseReluDense.wi_1.weight', 'decoder.block.2.layer.2.DenseReluDense.wi_0.weight', 'decoder.block.10.layer.2.DenseReluDense.wi_0.weight', 'encoder.block.4.layer.1.DenseReluDense.wi_0.weight', 'encoder.block.8.layer.1.DenseReluDense.wi_0.weight', 'decoder.block.5.layer.2.DenseReluDense.wi_0.weight', 'encoder.block.2.layer.1.DenseReluDense.wi_1.weight', 'encoder.block.3.layer.1.DenseReluDense.wi_1.weight', 'decoder.block.0.layer.2.DenseReluDense.wi_0.weight', 'encoder.block.11.layer.1.DenseReluDense.wi_0.weight', 'decoder.block.8.layer.2.DenseReluDense.wi_0.weight', 'decoder.block.9.layer.2.DenseReluDense.wi_1.weight', 'encoder.block.6.layer.1.DenseReluDense.wi_1.weight', 'encoder.block.0.layer.1.DenseReluDense.wi_1.weight', 'decoder.block.6.layer.2.DenseReluDense.wi_0.weight', 'encoder.block.6.layer.1.DenseReluDense.wi_0.weight', 'encoder.block.3.layer.1.DenseReluDense.wi_0.weight', 'encoder.block.9.layer.1.DenseReluDense.wi_0.weight', 'encoder.block.0.layer.1.DenseReluDense.wi_0.weight', 'encoder.block.10.layer.1.DenseReluDense.wi_0.weight', 'decoder.block.1.layer.2.DenseReluDense.wi_0.weight', 'decoder.block.9.layer.2.DenseReluDense.wi_0.weight', 'decoder.block.7.layer.2.DenseReluDense.wi_1.weight', 'encoder.block.2.layer.1.DenseReluDense.wi_0.weight', 'encoder.block.9.layer.1.DenseReluDense.wi_1.weight', 'encoder.block.10.layer.1.DenseReluDense.wi_1.weight', 'decoder.block.4.layer.2.DenseReluDense.wi_1.weight', 'decoder.block.6.layer.2.DenseReluDense.wi_1.weight', 'decoder.block.8.layer.2.DenseReluDense.wi_1.weight', 'decoder.block.11.layer.2.DenseReluDense.wi_0.weight', 'decoder.block.10.layer.2.DenseReluDense.wi_1.weight', 'encoder.block.4.layer.1.DenseReluDense.wi_1.weight', 'encoder.block.1.layer.1.DenseReluDense.wi_1.weight', 'decoder.block.3.layer.2.DenseReluDense.wi_1.weight']

• This IS expected if you are initializing T5ForConditionalGeneration 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 T5ForConditionalGeneration from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
  Some weights of T5ForConditionalGeneration were not initialized from the model checkpoint at /home/.../checkpoint-pt-60001/ and are newly initialized: ['encoder.block.8.layer.1.DenseReluDense.wi.weight', 'decoder.block.11.layer.2.DenseReluDense.wi.weight', 'decoder.block.4.layer.2.DenseReluDense.wi.weight', 'encoder.block.2.layer.1.DenseReluDense.wi.weight', 'encoder.block.10.layer.1.DenseReluDense.wi.weight', 'decoder.block.1.layer.2.DenseReluDense.wi.weight', 'encoder.block.11.layer.1.DenseReluDense.wi.weight', 'decoder.block.3.layer.2.DenseReluDense.wi.weight', 'encoder.block.0.layer.1.DenseReluDense.wi.weight', 'encoder.block.3.layer.1.DenseReluDense.wi.weight', 'decoder.block.6.layer.2.DenseReluDense.wi.weight', 'encoder.block.6.layer.1.DenseReluDense.wi.weight', 'decoder.block.10.layer.2.DenseReluDense.wi.weight', 'decoder.block.9.layer.2.DenseReluDense.wi.weight', 'encoder.block.5.layer.1.DenseReluDense.wi.weight', 'decoder.block.8.layer.2.DenseReluDense.wi.weight', 'encoder.block.7.layer.1.DenseReluDense.wi.weight', 'decoder.block.0.layer.2.DenseReluDense.wi.weight', 'decoder.block.2.layer.2.DenseReluDense.wi.weight', 'encoder.block.9.layer.1.DenseReluDense.wi.weight', 'decoder.block.7.layer.2.DenseReluDense.wi.weight', 'encoder.block.1.layer.1.DenseReluDense.wi.weight', 'decoder.block.5.layer.2.DenseReluDense.wi.weight', 'encoder.block.4.layer.1.DenseReluDense.wi.weight']

You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
Some weights of T5ForConditionalGeneration were not initialized from the model checkpoint at /home/.../checkpoint-pt-60001/ and are newly initialized because the shapes did not match:

• shared.weight: found shape torch.Size([32128, 768]) in the checkpoint and torch.Size([32102, 768]) in the model instantiated
• encoder.embed_tokens.weight: found shape torch.Size([32128, 768]) in the checkpoint and torch.Size([32102, 768]) in the model instantiated

[PiotrNawrot]

Make sure you're using the same config for both pre-training and fine-tuning. google/t5-v1_1-base which is the default config we download from HF uses vocab size of 32128 and gated-gelu FeedForward network.