nyu-mll/glue
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How to use davidliu1110/bert-fine-tuned-cola with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="davidliu1110/bert-fine-tuned-cola") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("davidliu1110/bert-fine-tuned-cola")
model = AutoModelForSequenceClassification.from_pretrained("davidliu1110/bert-fine-tuned-cola", device_map="auto")This model is a fine-tuned version of bert-base-uncased 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 |
|---|---|---|---|
| No log | 1.0 | 459 | 0.4187 |
| 0.5148 | 2.0 | 918 | 0.5389 |
| 0.3202 | 3.0 | 1377 | 0.6432 |
| 0.1684 | 4.0 | 1836 | 0.7600 |
| 0.101 | 5.0 | 2295 | 0.8369 |