rajpurkar/squad_v2
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How to use intanm/mbert-squad2-webis 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="intanm/mbert-squad2-webis") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("intanm/mbert-squad2-webis")
model = AutoModelForQuestionAnswering.from_pretrained("intanm/mbert-squad2-webis", device_map="auto")This model is a fine-tuned version of intanm/mbert-squadv2 on the None dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 200 | 2.8065 |
| No log | 2.0 | 400 | 2.8088 |
| 2.5698 | 3.0 | 600 | 3.1652 |
| 2.5698 | 4.0 | 800 | 3.5464 |
| 1.1384 | 5.0 | 1000 | 3.8477 |
| 1.1384 | 6.0 | 1200 | 4.1725 |
| 1.1384 | 7.0 | 1400 | 4.5057 |
| 0.4763 | 8.0 | 1600 | 4.7721 |
| 0.4763 | 9.0 | 1800 | 4.8970 |
| 0.2594 | 10.0 | 2000 | 4.8747 |