book_reviews_model_light

---

library_name: transformers license: apache-2.0 base_model: bert-base-uncased tags:

• generated_from_trainer datasets:
• amazon-reviews-2023 model-index:
• name: book_reviews_model results: []

---

Book Reviews Classification Model

Model Description

This model is a fine-tuned version of bert-base-uncased on the amazon-reviews-2023 dataset for classifying book reviews into star ratings (1-5).

Model Details

• Task: Single-label Text Classification
• Input: Book review text
• Output: Star rating (1-5)

Performance Metrics

• Accuracy: 0.7537
• Evaluation Loss: 0.7654

Training Hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3.0

Framework Versions

• Transformers 4.46.2
• Pytorch 2.5.1+cu121
• Datasets 3.1.0
• Tokenizers 0.20.3

Intended Uses

Classify book reviews into star ratings based on review content.

Limitations

• Trained on Amazon book reviews dataset
• Performance may vary on out-of-domain text

Inference Example

from transformers import pipeline

classifier = pipeline("text-classification", model="your-username/book_reviews_model")
result = classifier("This book was an incredible read!")