Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use pritamdeka/PubMedBERT-MNLI-MedNLI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pritamdeka/PubMedBERT-MNLI-MedNLI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pritamdeka/PubMedBERT-MNLI-MedNLI")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pritamdeka/PubMedBERT-MNLI-MedNLI") model = AutoModelForSequenceClassification.from_pretrained("pritamdeka/PubMedBERT-MNLI-MedNLI") - Inference
- Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 20.0, | |
| "eval_accuracy": 0.8666666746139526, | |
| "eval_loss": 0.9500740170478821, | |
| "eval_runtime": 13.4036, | |
| "eval_samples": 1395, | |
| "eval_samples_per_second": 104.076, | |
| "eval_steps_per_second": 3.283, | |
| "train_loss": 0.10057472327884626, | |
| "train_runtime": 6733.6679, | |
| "train_samples": 11232, | |
| "train_samples_per_second": 33.361, | |
| "train_steps_per_second": 1.043 | |
| } |