Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
English
roberta
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use JeremiahZ/roberta-base-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JeremiahZ/roberta-base-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JeremiahZ/roberta-base-mrpc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JeremiahZ/roberta-base-mrpc") model = AutoModelForSequenceClassification.from_pretrained("JeremiahZ/roberta-base-mrpc") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 5.0, | |
| "eval_accuracy": 0.9019607843137255, | |
| "eval_combined_score": 0.9157691245512289, | |
| "eval_f1": 0.9295774647887324, | |
| "eval_loss": 0.4898183345794678, | |
| "eval_runtime": 0.8404, | |
| "eval_samples": 408, | |
| "eval_samples_per_second": 485.493, | |
| "eval_steps_per_second": 60.687 | |
| } |