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README.md

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+# BART-Based Text Summarization Model for News Aggregation
+
+This repository hosts a BART transformer model fine-tuned for abstractive text summarization of news articles. It is designed to condense lengthy news reports into concise, informative summaries, enhancing user experience for news readers and aggregators.
+
+## Model Details
+
+- **Model Architecture:** BART (Facebook's BART-base)
+- **Task:** Abstractive Text Summarization
+- **Domain:** News Articles
+- **Dataset:** Reddit-TIFU (Hugging Face Datasets)
+- **Fine-tuning Framework:** Hugging Face Transformers
+
+## Usage
+
+### Installation
+
+```bash
+pip install datasets transformers rouge-score evaluate
+```
+
+### Loading the Model
+
+```python
+from transformers import BartTokenizer, BartForConditionalGeneration, Trainer, TrainingArguments, DataCollatorForSeq2Seq
+import torch
+
+# Load tokenizer and model
+device = 'cuda' if torch.cuda.is_available() else 'cpu'
+model_name = "facebook/bart-base"  
+tokenizer = BartTokenizer.from_pretrained(model_name)
+model = BartForConditionalGeneration.from_pretrained(model_name).to(device)
+```
+
+## Performance Metrics
+
+- **Rouge1 :** 25.500000
+- **Rouge2 :** 7.860000
+- **Rougel :** 20.640000
+- **Rougelsum :** 21.180000
+
+
+## Fine-Tuning Details
+
+### Dataset
+
+The dataset is sourced from Hugging Face’s Reddit-TIFU dataset. It contains 79,000 reddit post and their summaries.
+The original training and testing sets were merged, shuffled, and re-split using an 90/10 ratio.
+
+### Training Configuration
+
+- **Epochs:** 3
+- **Batch Size:** 8
+- **Learning Rate:** 2e-5
+- **Evaluation Strategy:** epoch
+
+### Quantization
+ 
+Post-training quantization was applied using PyTorch's built-in quantization framework to reduce the model size and improve inference efficiency.
+
+## Repository Structure
+
+```
+.
+├── config.json
+├── tokenizer_config.json    
+├── sepcial_tokens_map.json 
+├── tokenizer.json        
+├── model.safetensors    # Fine Tuned Model
+├── README.md            # Model documentation
+```
+
+## Limitations
+ 
+- The model may not generalize well to domains outside the fine-tuning dataset.  
+
+- Quantization may result in minor accuracy degradation compared to full-precision models.  
+ 
+## Contributing
+ 
+Contributions are welcome! Feel free to open an issue or submit a pull request if you have suggestions or improvements.

special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "cls_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "<mask>",
+    "lstrip": true,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<pad>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<pad>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "3": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "50264": {
+      "content": "<mask>",
+      "lstrip": true,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": false,
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "errors": "replace",
+  "extra_special_tokens": {},
+  "mask_token": "<mask>",
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "tokenizer_class": "BartTokenizer",
+  "unk_token": "<unk>"
+}