nyu-mll/glue
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How to use zack-paperspace/roberta-base-finetuned-cola with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="zack-paperspace/roberta-base-finetuned-cola") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("zack-paperspace/roberta-base-finetuned-cola")
model = AutoModelForSequenceClassification.from_pretrained("zack-paperspace/roberta-base-finetuned-cola", device_map="auto")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 |
|---|---|---|---|---|
| 0.5211 | 1.0 | 534 | 0.4031 | 0.5599 |
| 0.3739 | 2.0 | 1068 | 0.4688 | 0.5713 |
| 0.0697 | 3.0 | 1602 | 0.4988 | 0.6070 |
| 0.0712 | 4.0 | 2136 | 0.5596 | 0.6221 |
| 0.0955 | 5.0 | 2670 | 0.5732 | 0.6495 |