nyu-mll/glue
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How to use jxuhf/roberta-base-finetuned-cola with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="jxuhf/roberta-base-finetuned-cola") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("jxuhf/roberta-base-finetuned-cola")
model = AutoModelForSequenceClassification.from_pretrained("jxuhf/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:
More information needed
from transformers import AutoModelForSequenceClassification
model = AutoModelForSequenceClassification.from_pretrained("jxuhf/roberta-base-finetuned-cola")
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|---|---|---|---|---|
| 0.4981 | 1.0 | 535 | 0.5162 | 0.5081 |
| 0.314 | 2.0 | 1070 | 0.4716 | 0.5579 |