Text Classification
Transformers
PyTorch
roberta
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use nfliu/roberta-large_boolq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nfliu/roberta-large_boolq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nfliu/roberta-large_boolq")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nfliu/roberta-large_boolq") model = AutoModelForSequenceClassification.from_pretrained("nfliu/roberta-large_boolq", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 5.0, | |
| "eval_accuracy": 0.8568807339449541, | |
| "eval_loss": 0.6057409644126892, | |
| "eval_runtime": 33.2631, | |
| "eval_samples": 3270, | |
| "eval_samples_per_second": 98.307, | |
| "eval_steps_per_second": 12.296, | |
| "train_loss": 0.2942116430250265, | |
| "train_runtime": 1876.9877, | |
| "train_samples": 9427, | |
| "train_samples_per_second": 25.112, | |
| "train_steps_per_second": 0.786 | |
| } |