Token Classification
Transformers
PyTorch
Safetensors
xlm-roberta
Generated from Trainer
Eval Results (legacy)
Instructions to use universalner/uner_all with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use universalner/uner_all with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="universalner/uner_all")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("universalner/uner_all") model = AutoModelForTokenClassification.from_pretrained("universalner/uner_all", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 347 Bytes
d22837a | 1 2 3 4 5 6 7 8 9 10 11 12 | {
"epoch": 5.0,
"eval_accuracy": 0.9842612991521463,
"eval_f1": 0.8544453186467348,
"eval_loss": 0.11804134398698807,
"eval_precision": 0.8566170026292725,
"eval_recall": 0.8522846180676665,
"eval_runtime": 39.8443,
"eval_samples": 6773,
"eval_samples_per_second": 169.987,
"eval_steps_per_second": 42.515
} |