nyu-mll/glue
Viewer • Updated • 1.49M • 452k • 504
How to use Jofiel/Practica2 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="Jofiel/Practica2") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("Jofiel/Practica2")
model = AutoModelForSequenceClassification.from_pretrained("Jofiel/Practica2")This model is a fine-tuned version of distilroberta-base 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 | F1 |
|---|---|---|---|---|---|
| 0.5334 | 1.09 | 500 | 0.4107 | 0.8284 | 0.8708 |
| 0.366 | 2.18 | 1000 | 0.6723 | 0.8480 | 0.8931 |
Base model
distilbert/distilroberta-base