stanfordnlp/squad_adversarial
Updated • 480 • 10
How to use nidhinthomas/AdQuest-when-how-many with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("question-answering", model="nidhinthomas/AdQuest-when-how-many") # Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("nidhinthomas/AdQuest-when-how-many")
model = AutoModelForQuestionAnswering.from_pretrained("nidhinthomas/AdQuest-when-how-many")This model is a fine-tuned version of nidhinthomas/electra-small-squad-finetuned-synQA on the squad_adversarial dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.0179 | 1.0 | 3320 | 2.2782 |
| 0.9379 | 2.0 | 6640 | 2.3738 |
| 0.8668 | 3.0 | 9960 | 2.5231 |