transformers safetensors bart text2text-generation arxiv:1910.09700 autotrain_compatible endpoints_compatible region:us
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library_name: transformers
tags: []
---

# Model Card for Model ID

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## Model Details

### Model Description
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This is a fine-tuned BART model for summarizing Amazon reviews, fine-tuned on the amazon_review_multi dataset using Hugging Face's transformers library. It supports summarization in English and Spanish, generating concise and meaningful summaries from review text.

- **Developed by:** Shubhangi Nikam and Asmita Singh
- **Funded by [optional]:** NA
- **Shared by [optional]:** 
- **Model type:** Sequence-to-sequence Transformer for text summarization
- **Language(s) (NLP):** Python
- **License:**  Apache 2.0 (inheritance from the original model and dataset)
- **Finetuned from model [optional]:** xonic48/amazon_review_multi

### Model Sources [optional]

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- **Repository:** asingh14/bart-finetuned-amazon_review_multi
- **Paper [optional]:** 
- **Demo [optional]:**


## To test the code on google collab run the below code.
from transformers import pipeline

# Load the summarization pipeline using google/mt5-small model
summarizer = pipeline("summarization", model="asingh14/bart-finetuned-amazon_review_multi")

# Text to summarize
text = """
The cow is a domestic animal widely regarded as a symbol of utility, patience, and nurturing across many cultures. Known for its docile nature and adaptability, the cow has been an integral part of human civilization for thousands of years. It provides essential products such as milk, which is a rich source of nutrition, including proteins, calcium, and vitamins. Milk-derived products like butter, cheese, and yogurt further enhance its importance in our daily lives.

In many agrarian societies, cows are vital for farming. They are used as draft animals to plow fields and transport goods. Additionally, cow dung serves as a natural fertilizer, enriching the soil and boosting agricultural productivity, while also being utilized as a biofuel in rural areas.

The cow holds special cultural and religious significance, especially in India, where it is revered as a sacred animal. It symbolizes purity and selflessness, often being associated with motherhood for its nurturing role.

Despite its contributions, the cow requires proper care, including adequate food, clean water, and shelter. Protecting cows from exploitation and ensuring their well-being is a shared responsibility.

Thus, the cow is not just an animal but a benefactor to humanity, deserving respect and gratitude for its immeasurable contributions.
"""

# Get the summary
summary = summarizer(text)

# Print the summarized text
for s in summary:
    print(s['summary_text'])


# The o/p should be a summary of the above given text.
cow is a domestic animal widely regarded as a symbol of utility, patience, and nurturing across many cultures. Known for its docile nature and adaptability, the cow has been an integral part of human civilization for thousands of years. Protecting cows from exploitation and ensuring their well-being is a shared responsibility


## Uses

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### Direct Use

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This model can be used to generate concise summaries for product reviews. Use cases include e-commerce platforms, review aggregation websites, or research requiring textual analysis of customer reviews.

[More Information Needed]

### Downstream Use [optional]

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This model could be integrated into broader applications such as customer feedback analysis tools, sentiment analysis pipelines, or any system requiring review summarization.

[More Information Needed]

### Out-of-Scope Use

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This model is not designed for summarizing texts unrelated to customer reviews. Using it for other languages or domains without further fine-tuning may result in suboptimal performance.

[More Information Needed]

## Bias, Risks, and Limitations

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The model may introduce biases inherent in the dataset, such as language-specific nuances or cultural assumptions.
Summaries may occasionally miss critical details or contain hallucinations, as is common with sequence-to-sequence models.


### Recommendations

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Users should review the generated summaries, especially if used in critical or customer-facing applications.

## How to Get Started with the Model

Use the code below to get started with the model.

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## Training Details

### Training Data

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The model was fine-tuned on the amazon_review_multi dataset from Hugging Face's datasets library. The dataset contains multilingual product reviews with summaries in English and Spanish.


### Training Procedure

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#### Preprocessing [optional]

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#### Training Hyperparameters

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#### Speeds, Sizes, Times [optional]

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## Evaluation

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### Testing Data, Factors & Metrics

#### Testing Data

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#### Factors

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#### Metrics

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### Results

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#### Summary



## Model Examination [optional]

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## Environmental Impact

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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

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## Technical Specifications [optional]

### Model Architecture and Objective

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#### Software

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## Citation [optional]

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## Glossary [optional]

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