nyu-mll/glue
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How to use Tomor0720/deberta-base-finetuned-sst2 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="Tomor0720/deberta-base-finetuned-sst2") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("Tomor0720/deberta-base-finetuned-sst2")
model = AutoModelForSequenceClassification.from_pretrained("Tomor0720/deberta-base-finetuned-sst2")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 |
|---|---|---|---|---|
| 0.1946 | 1.0 | 4210 | 0.2586 | 0.9278 |
| 0.1434 | 2.0 | 8420 | 0.2296 | 0.9472 |
| 0.1025 | 3.0 | 12630 | 0.2411 | 0.9495 |