nyu-mll/glue
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How to use dunlp/GWW-finetuned-cola with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="dunlp/GWW-finetuned-cola") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("dunlp/GWW-finetuned-cola")
model = AutoModelForSequenceClassification.from_pretrained("dunlp/GWW-finetuned-cola")This model is a fine-tuned version of dunlp/GWW 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 | Matthews Correlation |
|---|---|---|---|---|
| 0.6181 | 1.0 | 535 | 0.6585 | 0.0 |
| 0.5938 | 2.0 | 1070 | 0.6276 | 0.0511 |
| 0.5241 | 3.0 | 1605 | 0.6609 | 0.1696 |
| 0.4433 | 4.0 | 2140 | 0.8239 | 0.1432 |
| 0.3492 | 5.0 | 2675 | 0.9236 | 0.1351 |