rcds/swiss_judgment_prediction
Updated • 351 • 15
How to use mhmmterts/my_model_all with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="mhmmterts/my_model_all") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("mhmmterts/my_model_all")
model = AutoModelForSequenceClassification.from_pretrained("mhmmterts/my_model_all")This model is a fine-tuned version of joelniklaus/legal-swiss-roberta-large on the swiss_judgment_prediction 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 |
|---|---|---|---|---|
| 0.5561 | 1.0 | 1866 | 0.5090 | 0.8081 |
| 0.5522 | 2.0 | 3732 | 0.4914 | 0.8081 |
Base model
joelniklaus/legal-swiss-roberta-large