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How to use JFernandoGRE/classificator_names with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="JFernandoGRE/classificator_names") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("JFernandoGRE/classificator_names")
model = AutoModelForSequenceClassification.from_pretrained("JFernandoGRE/classificator_names")This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-uncased on the None 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 |
|---|---|---|---|---|
| No log | 1.0 | 88 | 0.0798 | 0.9867 |
| No log | 2.0 | 176 | 0.0745 | 0.9867 |
| No log | 3.0 | 264 | 0.0770 | 0.9867 |
Base model
dccuchile/bert-base-spanish-wwm-uncased