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") - Notebooks
- Google Colab
- Kaggle
| { | |
| "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 | |
| } |