KamilHugsFaces/clay-modernbert-v1

ModernBERT Fine-tuned for Binary Classification

This model is a fine-tuned version of answerdotai/ModernBERT-base for binary classification.

Training Details

• Training epochs: 3
• Batch size: 16
• Learning rate: 2e-05
• Training samples: 800
• Validation samples: 200

Evaluation Results

• Accuracy: 0.4400
• Precision: 0.9333
• Recall: 0.4421
• F1 Score: 0.6000

Usage

from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch

tokenizer = AutoTokenizer.from_pretrained("KamilHugsFaces/clay-modernbert-v1")
model = AutoModelForSequenceClassification.from_pretrained("KamilHugsFaces/clay-modernbert-v1")

text = "Your text here"
inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=512)

with torch.no_grad():
    outputs = model(**inputs)
    prediction = torch.argmax(outputs.logits, dim=-1).item()
    probabilities = torch.softmax(outputs.logits, dim=-1)[0]

print(f"Prediction: {prediction}")
print(f"Confidence: {probabilities[prediction]:.4f}")