Instructions to use zeyadusf/deberta-DAIGT-MODELS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zeyadusf/deberta-DAIGT-MODELS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="zeyadusf/deberta-DAIGT-MODELS")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("zeyadusf/deberta-DAIGT-MODELS") model = AutoModelForSequenceClassification.from_pretrained("zeyadusf/deberta-DAIGT-MODELS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
library_name: transformers
tags:
- 'nlp '
- classification
license: apache-2.0
datasets:
- zeyadusf/daigt
language:
- en
base_model:
- microsoft/deberta-base
pipeline_tag: text-classification
Model Card for Model ID
Model Details
- eval_loss : 0.0035623444709926844,
- eval_accuracy : 0.9996336996336996,
- eval_f1-score : 0.999633699584551,
- epoch : 2
Classification Report:
precision recall f1-score support
0 1.00 1.00 1.00 1365
1 1.00 1.00 1.00 1365
accuracy 1.00 2730
macro avg 1.00 1.00 1.00 2730
weighted avg 1.00 1.00 1.00 2730
