rajpurkar/squad
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How to use camie-cool-2903/contextuality with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("question-answering", model="camie-cool-2903/contextuality") # Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("camie-cool-2903/contextuality")
model = AutoModelForQuestionAnswering.from_pretrained("camie-cool-2903/contextuality", 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 |
|---|---|---|---|
| No log | 1.0 | 250 | 2.4234 |
| 2.833 | 2.0 | 500 | 1.7814 |
| 2.833 | 3.0 | 750 | 1.5995 |
| 1.2171 | 4.0 | 1000 | 1.6382 |
| 1.2171 | 5.0 | 1250 | 1.6340 |
Base model
distilbert/distilbert-base-uncased