nyu-mll/glue
Viewer • Updated • 1.49M • 480k • 498
How to use anirudh21/xlnet-base-cased-finetuned-wnli with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="anirudh21/xlnet-base-cased-finetuned-wnli") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("anirudh21/xlnet-base-cased-finetuned-wnli")
model = AutoModelForSequenceClassification.from_pretrained("anirudh21/xlnet-base-cased-finetuned-wnli")This model is a fine-tuned version of xlnet-base-cased on the glue 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 | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 40 | 0.7209 | 0.5352 |
| No log | 2.0 | 80 | 0.6874 | 0.5634 |
| No log | 3.0 | 120 | 0.6908 | 0.5634 |
| No log | 4.0 | 160 | 0.6987 | 0.4930 |
| No log | 5.0 | 200 | 0.6952 | 0.5634 |