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AdamCodd
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bart-large-cnn-samsum

Summarization
Transformers
PyTorch
ONNX
Safetensors
bart
text2text-generation
Generated from Trainer
seq2seq
Eval Results
Inference Endpoints
Model card Files Community
2
bart-large-cnn-samsum
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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: bart-large-cnn-samsum
  results:
  - task:
      type: summarization
      name: Summarization
    dataset:
      name: 'SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization'
      type: samsum
    metrics:
    - type: rogue-1
      value: 43.6283
      name: Validation ROGUE-1
    - type: rogue-2
      value: 19.3096
      name: Validation ROGUE-2
    - type: rogue-l
      value: 41.2140
      name: Validation ROGUE-L
---

# bart-large-cnn-samsum

This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 0.755
- Rouge1: 43.6283
- Rouge2: 19.3096
- Rougel: 41.2140
- Rougelsum: 37.2590

## Model description

More information needed

## Intended uses & limitations

```python
from transformers import pipeline
summarizer = pipeline("summarization", model="AdamCodd/bart-large-cnn-samsum")

conversation = '''Sugi: I am tired of everything in my life.
Tommy: What? How happy your life is! I do envy you.
Sugi: You don't know that I have been overprotected by my mother these years. I am really about to leave the family and spread my wings.
Tommy: Maybe you are right.                                         
'''
summarizer(conversation)
```

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 1270
- optimizer: AdamW with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 150
- num_epochs: 1

### Training results

| key | value |
| --- | ----- |
| eval_rouge1 | 43.6283 |
| eval_rouge2 | 19.3096 |
| eval_rougeL | 41.2140 |
| eval_rougeLsum | 37.2590 |

### Framework versions

- Transformers 4.33.2
- Pytorch lightning 2.0.9
- Tokenizers 0.13.3