nyu-mll/glue
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How to use Isaac18/practica2_imc with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="Isaac18/practica2_imc") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("Isaac18/practica2_imc")
model = AutoModelForSequenceClassification.from_pretrained("Isaac18/practica2_imc")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 |
|---|---|---|---|---|---|
| 0.5331 | 1.09 | 500 | 0.5300 | 0.8211 | 0.8781 |
| 0.3465 | 2.18 | 1000 | 0.6891 | 0.8382 | 0.8866 |
Base model
distilbert/distilroberta-base