nyu-mll/glue
Viewer • Updated • 1.49M • 463k • 495
How to use arbazk/distilbert-base-uncased-finetuned-cola with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="arbazk/distilbert-base-uncased-finetuned-cola") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("arbazk/distilbert-base-uncased-finetuned-cola")
model = AutoModelForSequenceClassification.from_pretrained("arbazk/distilbert-base-uncased-finetuned-cola")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 |
|---|---|---|---|---|
| 0.5265 | 1.0 | 535 | 0.5547 | 0.4112 |
| 0.3497 | 2.0 | 1070 | 0.5017 | 0.4919 |
| 0.2307 | 3.0 | 1605 | 0.5383 | 0.5482 |
| 0.1734 | 4.0 | 2140 | 0.8100 | 0.5387 |
| 0.1336 | 5.0 | 2675 | 0.8376 | 0.5498 |