bart_samsum / README.md
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---
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart_samsum
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bart_samsum
This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on [SAMSUM](https://huggingface.co/datasets/samsum) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4966
- Rouge1: 41.4888
- Rouge2: 21.4374
- Rougel: 32.0455
- Rougelsum: 38.5273
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 0.525 | 0.54 | 500 | 0.5377 | 39.9053 | 20.1597 | 30.8845 | 37.3644 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.17.1
- Tokenizers 0.15.2