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---
library_name: transformers
license: apache-2.0
base_model: facebook/bart-large
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-summarizer
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-summarizer
This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1898
- Rouge1: 51.7683
- Rouge2: 36.3956
- Rougel: 45.7626
- Rougelsum: 45.7512
- Bert F1: 89.7697
## 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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bert F1 |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.48 | 1.0 | 766 | 2.3197 | 46.084 | 31.1672 | 40.7261 | 40.733 | 88.58 |
| 2.203 | 2.0 | 1532 | 2.2230 | 49.9815 | 34.8577 | 44.2515 | 44.2457 | 89.3509 |
| 2.1447 | 3.0 | 2298 | 2.1980 | 50.7333 | 35.3908 | 44.6146 | 44.6091 | 89.4589 |
| 2.0614 | 4.0 | 3064 | 2.1907 | 51.6468 | 36.4567 | 45.7548 | 45.7343 | 89.7909 |
| 2.0515 | 4.9941 | 3825 | 2.1898 | 51.7683 | 36.3956 | 45.7626 | 45.7512 | 89.7697 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0
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