nyu-mll/glue
Viewer • Updated • 1.49M • 484k • 498
How to use rriverar75/distilroberta-base-mrpc-glue with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="rriverar75/distilroberta-base-mrpc-glue") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("rriverar75/distilroberta-base-mrpc-glue")
model = AutoModelForSequenceClassification.from_pretrained("rriverar75/distilroberta-base-mrpc-glue")YAML Metadata Error:"widget[0].text" must be a string
YAML Metadata Error:"widget[1].text" must be a string
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 |
|---|---|---|---|---|---|
| 0.5523 | 1.09 | 500 | 0.3874 | 0.8333 | 0.8794 |
| 0.3421 | 2.18 | 1000 | 0.5895 | 0.8529 | 0.8969 |
Base model
distilbert/distilroberta-base