Text Classification
Transformers
PyTorch
TensorBoard
English
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use DunnBC22/roberta-base-Tweet_About_Disaster_Or_Not with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DunnBC22/roberta-base-Tweet_About_Disaster_Or_Not with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DunnBC22/roberta-base-Tweet_About_Disaster_Or_Not")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DunnBC22/roberta-base-Tweet_About_Disaster_Or_Not") model = AutoModelForSequenceClassification.from_pretrained("DunnBC22/roberta-base-Tweet_About_Disaster_Or_Not") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 5.0, | |
| "eval_F1": 0.7568710359408034, | |
| "eval_Precision": 0.7019607843137254, | |
| "eval_Recall": 0.8211009174311926, | |
| "eval_accuracy": 0.8988566402814424, | |
| "eval_loss": 0.26400184631347656, | |
| "eval_runtime": 92.2731, | |
| "eval_samples_per_second": 12.322, | |
| "eval_steps_per_second": 0.195 | |
| } |