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
File size: 403 Bytes
dfd0426 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"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
} |