nyu-mll/glue
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How to use JoseVallar01/practica2009 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="JoseVallar01/practica2009") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("JoseVallar01/practica2009")
model = AutoModelForSequenceClassification.from_pretrained("JoseVallar01/practica2009", device_map="auto")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 |
|---|---|---|---|---|---|
| 0.5107 | 1.09 | 500 | 0.4968 | 0.8333 | 0.8832 |
| 0.3606 | 2.18 | 1000 | 0.5264 | 0.8505 | 0.8909 |