Token Classification
Transformers
PyTorch
Spanish
roberta
PyTorch
Transformers
Token Classification
roberta-base-bne
Instructions to use sdocio/es_trf_ner_cds_bne-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sdocio/es_trf_ner_cds_bne-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="sdocio/es_trf_ner_cds_bne-base")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("sdocio/es_trf_ner_cds_bne-base") model = AutoModelForTokenClassification.from_pretrained("sdocio/es_trf_ner_cds_bne-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 528 Bytes
75e3f58 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
"epoch": 3.0,
"eval_accuracy": 0.9983546594777942,
"eval_f1": 0.9674450707465777,
"eval_loss": 0.007044909987598658,
"eval_precision": 0.9653351698806244,
"eval_recall": 0.9695642148950888,
"eval_runtime": 16.6647,
"eval_samples": 15178,
"eval_samples_per_second": 910.788,
"eval_steps_per_second": 113.893,
"train_loss": 0.009494402144574594,
"train_runtime": 283.3545,
"train_samples": 45533,
"train_samples_per_second": 482.078,
"train_steps_per_second": 15.066
} |