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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 5.0, | |
| "train_loss": 0.2764597121528957, | |
| "train_runtime": 134.1282, | |
| "train_samples": 3668, | |
| "train_samples_per_second": 136.735, | |
| "train_steps_per_second": 8.574 | |
| } |