rcds/swiss_judgment_prediction
Updated • 354 • 15
How to use mhmmterts/fine_tuned_model_balanced_512_tokens_it with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="mhmmterts/fine_tuned_model_balanced_512_tokens_it") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("mhmmterts/fine_tuned_model_balanced_512_tokens_it")
model = AutoModelForSequenceClassification.from_pretrained("mhmmterts/fine_tuned_model_balanced_512_tokens_it")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 |
|---|---|---|---|---|
| No log | 1.0 | 96 | 0.6889 | 0.6736 |
| No log | 2.0 | 192 | 0.7007 | 0.7771 |
Base model
joelniklaus/legal-swiss-roberta-large