Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
Trained with AutoTrain
text-embeddings-inference
Instructions to use Defensa2025/C2ROBERTA4060 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Defensa2025/C2ROBERTA4060 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Defensa2025/C2ROBERTA4060")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Defensa2025/C2ROBERTA4060") model = AutoModelForSequenceClassification.from_pretrained("Defensa2025/C2ROBERTA4060", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
library_name: transformers
tags:
- autotrain
- text-classification
base_model: xlm-roberta-base
widget:
- text: I love AutoTrain
Model Trained Using AutoTrain
- Problem type: Text Classification
Validation Metrics
loss: 0.30518293380737305
f1: 0.8927536231884058
precision: 0.9685534591194969
recall: 0.8279569892473119
auc: 0.9376422572796483
accuracy: 0.8854489164086687