nyu-mll/glue
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How to use Tomor0720/deberta-base-finetuned-qqp with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="Tomor0720/deberta-base-finetuned-qqp") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("Tomor0720/deberta-base-finetuned-qqp")
model = AutoModelForSequenceClassification.from_pretrained("Tomor0720/deberta-base-finetuned-qqp")This model is a fine-tuned version of microsoft/deberta-base on the glue 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 | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.2412 | 1.0 | 22741 | 0.2369 | 0.9048 | 0.8753 |
| 0.1742 | 2.0 | 45482 | 0.2617 | 0.9128 | 0.8844 |