distilbert-sentiment-imdb

UNKNOWN Fine-tuned for Sentiment Analysis

📊 Model Description

This model is a fine-tuned version of unknown for sentiment analysis on the UNKNOWN dataset.

Model Architecture: unknown
Task: Binary Sentiment Classification (Positive/Negative)
Language: English
Training Date: N/A

🎯 Performance Metrics

🔧 Training Details

Hyperparameters

{}

Dataset

• Training samples: N/A
• Validation samples: N/A
• Test samples: N/A

🚀 Usage

With Transformers Pipeline

from transformers import pipeline

# Load the model
classifier = pipeline("sentiment-analysis", model="YOUR_USERNAME/YOUR_MODEL_NAME")

# Predict
result = classifier("I love this movie!")
print(result)
# [{'label': 'POSITIVE', 'score': 0.9998}]

Manual Usage

from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch

# Load model and tokenizer
model_name = "YOUR_USERNAME/YOUR_MODEL_NAME"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSequenceClassification.from_pretrained(model_name)

# Prepare input
text = "This is an amazing product!"
inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=512)

# Predict
with torch.no_grad():
    outputs = model(**inputs)
    predictions = torch.nn.functional.softmax(outputs.logits, dim=-1)
    
# Get result
label_id = torch.argmax(predictions).item()
score = predictions[0][label_id].item()

labels = ["NEGATIVE", "POSITIVE"]
print(f"Label: {labels[label_id]}, Score: {score:.4f}")

📈 Training Curves

Training history visualization is available in the model files.

🏷️ Label Mapping

0: NEGATIVE
1: POSITIVE

⚙️ Model Configuration

{}

📝 Citation

If you use this model, please cite:

@misc{sentiment-model-unknown,
  author = {Your Name},
  title = {unknown Fine-tuned for Sentiment Analysis},
  year = {2025},
  publisher = {Hugging Face},
  howpublished = {\url{https://huggingface.co/YOUR_USERNAME/YOUR_MODEL_NAME}}
}

🤝 Contact

For questions or feedback, please open an issue in the repository.

📄 License

Apache 2.0

🔗 Related Models

• unknown

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