nyu-mll/glue
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How to use bonurtek/bert-base-uncased-finetuned-cola with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="bonurtek/bert-base-uncased-finetuned-cola") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("bonurtek/bert-base-uncased-finetuned-cola")
model = AutoModelForSequenceClassification.from_pretrained("bonurtek/bert-base-uncased-finetuned-cola")This model is a fine-tuned version of bert-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 | Matthews Correlation |
|---|---|---|---|---|
| No log | 1.0 | 268 | 0.4427 | 0.4984 |
| 0.398 | 2.0 | 536 | 0.4827 | 0.5880 |