nyu-mll/glue
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How to use Zaid/distilbert-base-uncased-finetuned-sst2 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="Zaid/distilbert-base-uncased-finetuned-sst2") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("Zaid/distilbert-base-uncased-finetuned-sst2")
model = AutoModelForSequenceClassification.from_pretrained("Zaid/distilbert-base-uncased-finetuned-sst2")This model is a fine-tuned version of distilbert-base-uncased 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 |
|---|---|---|---|---|
| 0.1777 | 1.0 | 4210 | 0.2863 | 0.9002 |