us-lsi/muchocine
Updated • 217 • 4
How to use raqdo09/clasificador-muchocine with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="raqdo09/clasificador-muchocine") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("raqdo09/clasificador-muchocine")
model = AutoModelForSequenceClassification.from_pretrained("raqdo09/clasificador-muchocine")This model is a fine-tuned version of mrm8488/electricidad-base-discriminator 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 | 388 | 1.3529 | 0.3871 |
| 1.3971 | 2.0 | 776 | 1.3244 | 0.4219 |
| 0.967 | 3.0 | 1164 | 1.4507 | 0.4284 |
Base model
mrm8488/electricidad-base-discriminator