nyu-mll/glue
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How to use ulichovick/platzi-distilroberta-base-mrpc-glue-Andres-Rojas with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="ulichovick/platzi-distilroberta-base-mrpc-glue-Andres-Rojas") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("ulichovick/platzi-distilroberta-base-mrpc-glue-Andres-Rojas")
model = AutoModelForSequenceClassification.from_pretrained("ulichovick/platzi-distilroberta-base-mrpc-glue-Andres-Rojas")This model is a fine-tuned version of distilroberta-base 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 | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.5194 | 1.09 | 500 | 0.5060 | 0.8309 | 0.8852 |
| 0.3535 | 2.18 | 1000 | 0.6370 | 0.8431 | 0.8849 |