nyu-mll/glue
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How to use Jinchen/roberta-base-finetuned-cola with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="Jinchen/roberta-base-finetuned-cola") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("Jinchen/roberta-base-finetuned-cola")
model = AutoModelForSequenceClassification.from_pretrained("Jinchen/roberta-base-finetuned-cola")This model is a fine-tuned version of roberta-base 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 |
|---|---|---|---|---|
| 0.4218 | 1.0 | 133 | 0.4236 | 0.5243 |
| 0.2077 | 2.0 | 266 | 0.3970 | 0.5930 |
| 0.184 | 3.0 | 399 | 0.4211 | 0.6279 |
| 0.1807 | 4.0 | 532 | 0.4854 | 0.6197 |
| 0.1405 | 5.0 | 665 | 0.5693 | 0.5968 |