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---
library_name: transformers
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
metrics:
- sacrebleu
- rouge
model-index:
- name: bart-base-finetuned-w-data-augm-4e-5
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-base-finetuned-w-data-augm-4e-5
This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3874
- Sacrebleu: 89.8161
- Rouge1: 95.6774
- Rouge2: 91.8937
- Rougel: 94.6649
- Rougelsum: 94.6595
- Bertscore Precision: 0.9414
- Bertscore Recall: 0.9376
- Bertscore F1: 0.9395
## 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: 4.4252514647201465e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Sacrebleu | Rouge1 | Rouge2 | Rougel | Rougelsum | Bertscore Precision | Bertscore Recall | Bertscore F1 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|:-------:|:-------:|:---------:|:-------------------:|:----------------:|:------------:|
| 0.1504 | 1.0 | 761 | 0.2797 | 90.9313 | 96.2421 | 92.8783 | 95.4262 | 95.4043 | 0.9496 | 0.9444 | 0.9469 |
| 0.0348 | 2.0 | 1522 | 0.2473 | 91.7583 | 96.3865 | 93.2655 | 95.6899 | 95.6811 | 0.9532 | 0.9504 | 0.9517 |
| 0.0587 | 3.0 | 2283 | 0.2413 | 91.828 | 96.4392 | 93.4124 | 95.7079 | 95.6976 | 0.9517 | 0.9508 | 0.9512 |
| 0.0269 | 4.0 | 3044 | 0.2588 | 91.9835 | 96.578 | 93.6221 | 95.8992 | 95.8798 | 0.9524 | 0.9527 | 0.9525 |
| 0.0439 | 5.0 | 3805 | 0.2678 | 92.1033 | 96.6815 | 93.6391 | 95.9677 | 95.9469 | 0.9544 | 0.9536 | 0.954 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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