|
--- |
|
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: [] |
|
--- |
|
|
|
--- |
|
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](https://huggingface.co/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 |
|
```python |
|
from transformers import pipeline |
|
|
|
classifier = pipeline("text-classification", model="your-username/book_reviews_model") |
|
result = classifier("This book was an incredible read!") |
|
|
