nyu-mll/glue
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How to use hoangthan/distilbert-base-uncased-finetuned-stsb with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="hoangthan/distilbert-base-uncased-finetuned-stsb") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("hoangthan/distilbert-base-uncased-finetuned-stsb")
model = AutoModelForSequenceClassification.from_pretrained("hoangthan/distilbert-base-uncased-finetuned-stsb", device_map="auto")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 | Pearson | Spearmanr |
|---|---|---|---|---|---|
| 1.1963 | 1.0 | 719 | 0.7779 | 0.8591 | 0.8582 |
| 0.5834 | 2.0 | 1438 | 0.6198 | 0.8684 | 0.8660 |
| 0.2718 | 3.0 | 2157 | 0.5497 | 0.8720 | 0.8684 |
| 0.2302 | 4.0 | 2876 | 0.5389 | 0.8738 | 0.8697 |
| 0.1505 | 5.0 | 3595 | 0.5508 | 0.8718 | 0.8679 |
Base model
distilbert/distilbert-base-uncased