Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Areepatw/roberta-multirc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Areepatw/roberta-multirc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Areepatw/roberta-multirc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Areepatw/roberta-multirc") model = AutoModelForSequenceClassification.from_pretrained("Areepatw/roberta-multirc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "model_name": "roberta-base", | |
| "dataset_name": "super_glue", | |
| "subset_name": "multirc", | |
| "eval_results": { | |
| "eval_loss": 0.6811200380325317, | |
| "eval_accuracy": 0.5738448844884488, | |
| "eval_f1": 0.43142386224389884, | |
| "eval_runtime": 70.1065, | |
| "eval_samples_per_second": 69.152, | |
| "eval_steps_per_second": 4.322, | |
| "epoch": 1.0 | |
| }, | |
| "accuracy": 0.5738448844884488, | |
| "f1": 0.43142386224389884 | |
| } |