nyu-mll/glue
Viewer • Updated • 1.49M • 449k • 525
How to use tuni/distilbert-base-uncased-finetuned-cola with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="tuni/distilbert-base-uncased-finetuned-cola") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("tuni/distilbert-base-uncased-finetuned-cola")
model = AutoModelForSequenceClassification.from_pretrained("tuni/distilbert-base-uncased-finetuned-cola", 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:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|---|---|---|---|---|
| 0.5227 | 1.0 | 535 | 0.5005 | 0.4121 |
| 0.318 | 2.0 | 1070 | 0.5265 | 0.4977 |
| 0.1887 | 3.0 | 1605 | 0.7035 | 0.5324 |