license: other
base_model: facebook/opt-350m
tags:
- generated_from_trainer
model-index:
- name: tmp_trainer
results: []
tmp_trainer
This model is a fine-tuned version of facebook/opt-350m on the addressWithContext dataset.
Model description
Make sure to set max_new_tokens = 20; otherwise, the model will generate one token at a time.
nlp = pipeline("text-generation", model="piazzola/tmp_trainer", max_new_tokens=20)
nlp("Landlord hereby demises unto Tenant, and Tenant hereby leases from Landlord for the terms and upon the conditions set forth in this Lease 30,600 square feet of space in the building located at 15 Firstfield Road, Gaithersburg, Maryland, the Building, as set forth on Exhibit A, hereto attached, said space being referred to as the Premises.")
Intended uses & limitations
The model is intended to detect addresses that occur in a sentence.
Training and evaluation data
This model is trained on piazzola/addressWithContext.
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1