Ahmadzei's picture
added 3 more tables for large emb model
5fa1a76
Train
Before you start training your model, create a map of the expected ids to their labels with id2label and label2id:
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",
}
label2id = {
"O": 0,
"B-corporation": 1,
"I-corporation": 2,
"B-creative-work": 3,
"I-creative-work": 4,
"B-group": 5,
"I-group": 6,
"B-location": 7,
"I-location": 8,
"B-person": 9,
"I-person": 10,
"B-product": 11,
"I-product": 12,
}
If you aren't familiar with finetuning a model with the [Trainer], take a look at the basic tutorial here!