nyu-mll/glue
Viewer • Updated • 1.49M • 485k • 498
How to use JeremiahZ/roberta-base-cola with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="JeremiahZ/roberta-base-cola") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("JeremiahZ/roberta-base-cola")
model = AutoModelForSequenceClassification.from_pretrained("JeremiahZ/roberta-base-cola")This model is a fine-tuned version of roberta-base on the GLUE COLA dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|---|---|---|---|---|
| 0.5497 | 1.0 | 535 | 0.5504 | 0.4613 |
| 0.3786 | 2.0 | 1070 | 0.4850 | 0.5470 |
| 0.2733 | 3.0 | 1605 | 0.5036 | 0.5792 |
| 0.2204 | 4.0 | 2140 | 0.5532 | 0.6139 |
| 0.164 | 5.0 | 2675 | 0.9516 | 0.5934 |
| 0.1351 | 6.0 | 3210 | 0.9051 | 0.5754 |
| 0.1065 | 7.0 | 3745 | 0.9006 | 0.6161 |
| 0.0874 | 8.0 | 4280 | 0.9457 | 0.6157 |
| 0.0579 | 9.0 | 4815 | 1.0372 | 0.6007 |
| 0.0451 | 10.0 | 5350 | 1.0571 | 0.6232 |