nyu-mll/glue
Viewer • Updated • 1.49M • 367k • 519
How to use platzi/platzi-distilroberta-base-mrpc-test with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="platzi/platzi-distilroberta-base-mrpc-test") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("platzi/platzi-distilroberta-base-mrpc-test")
model = AutoModelForSequenceClassification.from_pretrained("platzi/platzi-distilroberta-base-mrpc-test", device_map="auto")This model is a fine-tuned version of distilroberta-base on the datasetX 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 |
|---|---|---|---|---|---|
| 0.51 | 1.09 | 500 | 0.5825 | 0.8235 | 0.8696 |
| 0.342 | 2.18 | 1000 | 0.6815 | 0.8235 | 0.8686 |