Instructions to use MLRS/BERTu-ud-allennlp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- AllenNLP
How to use MLRS/BERTu-ud-allennlp with AllenNLP:
import allennlp_models from allennlp.predictors.predictor import Predictor predictor = Predictor.from_path("hf://MLRS/BERTu-ud-allennlp") - Notebooks
- Google Colab
- Kaggle
File size: 970 Bytes
933e371 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | {
"best_epoch": 59,
"peak_worker_0_memory_MB": 4387.515625,
"peak_gpu_0_memory_MB": 15878.68505859375,
"training_duration": "0:09:54.768662",
"training_start_epoch": 0,
"training_epochs": 78,
"epoch": 78,
"training_ud_UAS": 0.9929822815050766,
"training_ud_LAS": 0.9908421262193908,
"training_ud_UEM": 0.9073909171861086,
"training_ud_LEM": 0.8797862867319679,
"training_loss": 0.029289920917815633,
"training_worker_0_memory_MB": 4387.515625,
"training_gpu_0_memory_MB": 15878.68505859375,
"validation_ud_UAS": 0.9297203929612436,
"validation_ud_LAS": 0.8946345676346756,
"validation_ud_UEM": 0.3903002309468822,
"validation_ud_LEM": 0.23325635103926096,
"validation_loss": 1.351550132036209,
"best_validation_ud_UAS": 0.9311238259743064,
"best_validation_ud_LAS": 0.8967936953470798,
"best_validation_ud_UEM": 0.4018475750577367,
"best_validation_ud_LEM": 0.2471131639722864,
"best_validation_loss": 1.1966833174228668
} |