rajpurkar/squad
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How to use vxbrandon/my_awesome_qa_model with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("question-answering", model="vxbrandon/my_awesome_qa_model") # Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("vxbrandon/my_awesome_qa_model")
model = AutoModelForQuestionAnswering.from_pretrained("vxbrandon/my_awesome_qa_model", device_map="auto")This model is a fine-tuned version of distilbert-base-uncased on the squad 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 |
|---|---|---|---|
| 2.3143 | 1.0 | 685 | 1.3187 |
| 1.3356 | 2.0 | 1370 | 1.2095 |
| 1.0967 | 3.0 | 2055 | 1.1920 |
Base model
distilbert/distilbert-base-uncased