Judges
Collection
3 items • Updated
How to use JFernandoGRE/classificator_gender_judicialcases with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="JFernandoGRE/classificator_gender_judicialcases") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("JFernandoGRE/classificator_gender_judicialcases")
model = AutoModelForSequenceClassification.from_pretrained("JFernandoGRE/classificator_gender_judicialcases")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:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 213 | 0.0798 | 0.9829 |
| No log | 2.0 | 426 | 0.0780 | 0.9856 |
| 0.084 | 3.0 | 639 | 0.0874 | 0.9849 |
Base model
dccuchile/bert-base-spanish-wwm-uncased