Text Classification
Transformers
PyTorch
English
camembert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Intel/camembert-base-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Intel/camembert-base-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Intel/camembert-base-mrpc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Intel/camembert-base-mrpc") model = AutoModelForSequenceClassification.from_pretrained("Intel/camembert-base-mrpc") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 5.0, | |
| "eval_accuracy": 0.8504901960784313, | |
| "eval_combined_score": 0.8716422860884248, | |
| "eval_f1": 0.8927943760984183, | |
| "eval_loss": 0.4285973310470581, | |
| "eval_runtime": 9.7881, | |
| "eval_samples": 408, | |
| "eval_samples_per_second": 41.683, | |
| "eval_steps_per_second": 5.21, | |
| "train_loss": 0.38529563903808595, | |
| "train_runtime": 2014.3293, | |
| "train_samples": 3668, | |
| "train_samples_per_second": 9.105, | |
| "train_steps_per_second": 0.571 | |
| } |