rajpurkar/squad_v2
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How to use TurkuNLP/bert-base-finnish-cased-squad2 with Transformers:
# Use a pipeline as a high-level helper
# Warning: Pipeline type "question-answering" is no longer supported in transformers v5.
# You must load the model directly (see below) or downgrade to v4.x with:
# pip install "transformers<5.0.0"
from transformers import pipeline
pipe = pipeline("question-answering", model="TurkuNLP/bert-base-finnish-cased-squad2") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("TurkuNLP/bert-base-finnish-cased-squad2")
model = AutoModelForQuestionAnswering.from_pretrained("TurkuNLP/bert-base-finnish-cased-squad2", device_map="auto")This is the bert-base-finnish-cased-v1 model, fine-tuned using the Finnish SQuAD2.0 dataset. It's been trained on question-answer pairs, including unanswerable questions, for the task of Question Answering.
Language model: bert-base-finnish-v1
Language: Finnish
Downstream-task: Extractive QA
Training data: squad_v2_fi
Eval data: squad_v2_fi
batch_size = 12
n_epochs = 2
base_LM_model = "bert-base-finnish-cased-v1"
max_seq_len = 384
learning_rate = 3e-5
doc_stride=128
"exact": 68.2424,
"f1": 73.6607,
"HasAns_exact": 58.3290,
"HasAns_f1": 69.3629,
"HasAns_total": 5817,
"NoAns_exact": 77.8073,
"NoAns_f1": 77.8073,
"NoAns_total": 6029,
"samples": 12138,
"total": 11846
| model | F1 |
|---|---|
| TurkuNLP/bert-base-finnish-cased-squad2 | 73.66 |
| ilmariky/bert-base-finnish-cased-squad2-fi | 61.87 |