nyu-mll/glue
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How to use GCopoulos/deberta-finetuned-answer-polarity-7e-adj with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="GCopoulos/deberta-finetuned-answer-polarity-7e-adj") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("GCopoulos/deberta-finetuned-answer-polarity-7e-adj")
model = AutoModelForSequenceClassification.from_pretrained("GCopoulos/deberta-finetuned-answer-polarity-7e-adj")This model is a fine-tuned version of microsoft/deberta-large 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 | F1 |
|---|---|---|---|---|
| No log | 1.0 | 262 | 0.3918 | 0.8901 |
| 0.4372 | 2.0 | 524 | 0.4592 | 0.9138 |
| 0.4372 | 3.0 | 786 | 0.7605 | 0.8582 |