albertvillanova/legal_contracts
Viewer • Updated • 106k • 385 • 50
How to use muhtasham/bert-small-finetuned-legal-contracts-larger4010 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("fill-mask", model="muhtasham/bert-small-finetuned-legal-contracts-larger4010") # Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("muhtasham/bert-small-finetuned-legal-contracts-larger4010")
model = AutoModelForMaskedLM.from_pretrained("muhtasham/bert-small-finetuned-legal-contracts-larger4010")This model is a fine-tuned version of google/bert_uncased_L-4_H-512_A-8 on the None dataset.
More information needed
The model was not trained on the whole dataset which is around 9.5 GB, but only
The first 40% of train + the last 10% of train.
datasets_train = load_dataset('albertvillanova/legal_contracts' , split='train[:40%]')
datasets_validation = load_dataset('albertvillanova/legal_contracts' , split='train[-10%:]')
The following hyperparameters were used during training:
Base model
google/bert_uncased_L-4_H-512_A-8