nyu-mll/glue
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How to use platzi/platzi-distilroberta-base-mrpc-glue-luigitercero with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="platzi/platzi-distilroberta-base-mrpc-glue-luigitercero") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("platzi/platzi-distilroberta-base-mrpc-glue-luigitercero")
model = AutoModelForSequenceClassification.from_pretrained("platzi/platzi-distilroberta-base-mrpc-glue-luigitercero", 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:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.1853 | 1.09 | 500 | 0.6591 | 0.8431 | 0.8836 |
| 0.1812 | 2.18 | 1000 | 0.6591 | 0.8431 | 0.8836 |
Base model
distilbert/distilroberta-base