I’m trying to fine-tune dslim/bert-base-NER using the wnut_17 dataset.
Since the number of NER labels is different, I manually replaced these parameters in the model to get rid of the size mismatch error :
model.config.id2label = my_id2label
model.config.label2id = my_label2id
model.config._num_labels = len(my_id2label) ## replacing 9 by 13
However, when training starts I get the following error which I don’t know how to handle:

Expected input batch_size (1456) to match target batch_size (1008).

Has anyone handled this manually?
@sgugger @phosseini Won’t it be great if we can have a solid function that handles the head replacements for fine-tuning.
Shapes:

tokenized_wnut[‘train’].shape = (3394, 7)
tokenized_wnut[‘validation’].shape = (1009, 7)

Model config after “manual” modifications:
BertConfig {
  "_name_or_path": "dslim/bert-base-NER",
  "_num_labels": 13,
  "architectures": [
    "BertForTokenClassification"
  ],
  "attention_probs_dropout_prob": 0.1,
  "classifier_dropout": null,
  "hidden_act": "gelu",
  "hidden_dropout_prob": 0.1,
  "hidden_size": 768,
  "id2label": {
    "0": "O",
    "1": "B-corporation",
    "2": "I-corporation",
    "3": "B-creative-work",
    "4": "I-creative-work",
    "5": "B-group",
    "6": "I-group",
    "7": "B-location",
    "8": "I-location",
    "9": "B-person",
    "10": "I-person",
    "11": "B-product",
    "12": "I-product"
  },
  "initializer_range": 0.02,
  "intermediate_size": 3072,
  "label2id": {
    "B-corporation": 1,
    "B-creative-work": 3,
    "B-group": 5,
    "B-location": 7,
    "B-person": 9,
    "B-product": 11,
    "I-corporation": 2,
    "I-creative-work": 4,
    "I-group": 6,
    "I-location": 8,
    "I-person": 10,
    "I-product": 12,
    "O": 0
  },
  "layer_norm_eps": 1e-12,
  "max_position_embeddings": 512,
  "model_type": "bert",
  "num_attention_heads": 12,
  "num_hidden_layers": 12,
  "output_past": true,
  "pad_token_id": 0,
  "position_embedding_type": "absolute",
  "transformers_version": "4.14.1",
  "type_vocab_size": 2,
  "use_cache": true,
  "vocab_size": 28996
}