nyu-mll/glue
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How to use zhiyil/roberta-base-finetuned-cola with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="zhiyil/roberta-base-finetuned-cola") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("zhiyil/roberta-base-finetuned-cola")
model = AutoModelForSequenceClassification.from_pretrained("zhiyil/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 |
|---|---|---|---|---|
| 0.4536 | 1.0 | 534 | 0.4104 | 0.5738 |
| 0.4876 | 2.0 | 1068 | 0.5156 | 0.5729 |
| 0.1281 | 3.0 | 1602 | 0.5083 | 0.6145 |
| 0.0441 | 4.0 | 2136 | 0.5483 | 0.6119 |
| 0.2985 | 5.0 | 2670 | 0.6074 | 0.6221 |