UCLNLP/adversarial_qa
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How to use stevemobs/deberta-base-finetuned-squad1-aqa 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="stevemobs/deberta-base-finetuned-squad1-aqa") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("stevemobs/deberta-base-finetuned-squad1-aqa")
model = AutoModelForQuestionAnswering.from_pretrained("stevemobs/deberta-base-finetuned-squad1-aqa", device_map="auto")This model is a fine-tuned version of stevemobs/deberta-base-finetuned-squad1 on the adversarial_qa 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 |
|---|---|---|---|
| 1.9115 | 1.0 | 2527 | 1.5572 |
| 1.3429 | 2.0 | 5054 | 1.5912 |