nyu-mll/glue
Viewer • Updated • 1.49M • 856k • 1.1k
How to use guipiveti/distilbert-base-uncased-finetuned-cola with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="guipiveti/distilbert-base-uncased-finetuned-cola") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("guipiveti/distilbert-base-uncased-finetuned-cola")
model = AutoModelForSequenceClassification.from_pretrained("guipiveti/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 |
|---|---|---|---|---|
| 0.5181 | 1.0 | 535 | 0.4509 | 0.4539 |
| 0.3424 | 2.0 | 1070 | 0.4667 | 0.5190 |
| 0.2371 | 3.0 | 1605 | 0.6620 | 0.5026 |
| 0.1695 | 4.0 | 2140 | 0.7508 | 0.5427 |
| 0.1277 | 5.0 | 2675 | 0.8527 | 0.5252 |
Base model
distilbert/distilbert-base-uncased