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---
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart_CNN_NLP
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_CNN_NLP
This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co./facebook/bart-large-cnn) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.0479
- Rouge1: 45.8751
- Rouge2: 28.1917
- Rougel: 42.0922
- Rougelsum: 41.9934
- Gen Len: 6433791.8333
## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 4
- label_smoothing_factor: 0.1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:------------:|
| 3.1748 | 0.4 | 40 | 3.1564 | 44.8208 | 26.6733 | 41.2873 | 41.226 | 6433791.8889 |
| 3.0649 | 0.8 | 80 | 2.9386 | 45.8469 | 27.8327 | 41.8543 | 41.8139 | 6433791.8556 |
| 2.6983 | 1.2 | 120 | 2.8712 | 47.7681 | 29.8568 | 43.9396 | 43.8816 | 6433791.8778 |
| 2.6725 | 1.6 | 160 | 2.8698 | 46.6433 | 29.2504 | 43.1299 | 43.0348 | 6433791.9333 |
| 2.7537 | 2.0 | 200 | 2.8534 | 47.0645 | 29.6233 | 43.5479 | 43.4841 | 6433791.8778 |
| 2.3728 | 2.4 | 240 | 2.9305 | 46.1673 | 28.848 | 42.6293 | 42.5577 | 6433791.8889 |
| 2.3572 | 2.8 | 280 | 2.9414 | 47.2408 | 29.4202 | 43.4668 | 43.3747 | 6433791.9 |
| 2.087 | 3.2 | 320 | 3.0366 | 46.652 | 28.7844 | 42.7646 | 42.6204 | 6433791.8778 |
| 2.1212 | 3.6 | 360 | 3.0169 | 46.6902 | 28.1997 | 42.5114 | 42.4226 | 6433791.8222 |
| 2.1264 | 4.0 | 400 | 3.0479 | 45.8751 | 28.1917 | 42.0922 | 41.9934 | 6433791.8333 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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