LegalLMs
Collection
XLM-RoBERTa models with continued pretraining on the MultiLegalPile • 37 items • Updated • 4
How to use joelniklaus/legal-latvian-roberta-base with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("fill-mask", model="joelniklaus/legal-latvian-roberta-base") # Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("joelniklaus/legal-latvian-roberta-base")
model = AutoModelForMaskedLM.from_pretrained("joelniklaus/legal-latvian-roberta-base", device_map="auto")This model was trained from scratch on an unknown 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 |
|---|---|---|---|
| 0.9107 | 25.0 | 50000 | 0.6652 |
| 0.8619 | 50.01 | 100000 | 0.5780 |
| 0.8128 | 76.0 | 150000 | 0.5402 |
| 0.7458 | 101.01 | 200000 | 0.5318 |