Token Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
Eval Results (legacy)
Instructions to use Rodrigo1771/bsc-bio-ehr-es-cantemist-fasttext-75-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rodrigo1771/bsc-bio-ehr-es-cantemist-fasttext-75-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Rodrigo1771/bsc-bio-ehr-es-cantemist-fasttext-75-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Rodrigo1771/bsc-bio-ehr-es-cantemist-fasttext-75-ner") model = AutoModelForTokenClassification.from_pretrained("Rodrigo1771/bsc-bio-ehr-es-cantemist-fasttext-75-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 9.991889699918897, | |
| "eval_accuracy": 0.991867253328732, | |
| "eval_f1": 0.8512137823022711, | |
| "eval_loss": 0.047813717275857925, | |
| "eval_precision": 0.8462436745815493, | |
| "eval_recall": 0.8562426152028357, | |
| "eval_runtime": 15.6141, | |
| "eval_samples": 7354, | |
| "eval_samples_per_second": 470.984, | |
| "eval_steps_per_second": 58.921, | |
| "predict_accuracy": 0.9922143301576527, | |
| "predict_f1": 0.8534459275401798, | |
| "predict_loss": 0.044904835522174835, | |
| "predict_precision": 0.8332446808510638, | |
| "predict_recall": 0.8746510329424902, | |
| "predict_runtime": 23.1419, | |
| "predict_samples_per_second": 468.329, | |
| "predict_steps_per_second": 58.552, | |
| "total_flos": 1.919784837910831e+16, | |
| "train_loss": 0.008344567238123386, | |
| "train_runtime": 1725.5138, | |
| "train_samples": 39426, | |
| "train_samples_per_second": 228.488, | |
| "train_steps_per_second": 3.57 | |
| } |