---
library_name: transformers
license: apache-2.0
base_model: facebook/bart-large
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: bart-large-wiki-doc-full
  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-large-wiki-doc-full

This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.9843
- Sari: 51.0933
- Sari Add: 12.516
- Sari Keep: 45.354
- Sari Del: 95.4099
- Fkgl: 6.642
- Bleu: 19.5688
- D Sari: 0.4555
- D Sari Keep: 0.3857
- D Sari Del: 0.8046
- D Sari Add: 0.1763

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 15
- label_smoothing_factor: 0.3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Sari    | Sari Add | Sari Keep | Sari Del | Fkgl   | Bleu    | D Sari | D Sari Keep | D Sari Del | D Sari Add |
|:-------------:|:------:|:----:|:---------------:|:-------:|:--------:|:---------:|:--------:|:------:|:-------:|:------:|:-----------:|:----------:|:----------:|
| 5.6237        | 0.2862 | 500  | 5.1875          | 47.043  | 5.9566   | 40.0258   | 95.1466  | 7.2471 | 12.9924 | 0.4057 | 0.3169      | 0.7965     | 0.1038     |
| 5.0682        | 0.5725 | 1000 | 5.1042          | 48.192  | 9.0538   | 40.5192   | 95.0031  | 7.2139 | 15.7017 | 0.4288 | 0.3477      | 0.8055     | 0.1332     |
| 5.0363        | 0.8587 | 1500 | 5.0920          | 48.4536 | 9.2349   | 41.6306   | 94.4954  | 7.6174 | 20.3138 | 0.4245 | 0.3505      | 0.7871     | 0.1358     |
| 4.9284        | 1.1448 | 2000 | 5.0709          | 49.1161 | 9.9088   | 42.5012   | 94.9385  | 7.3117 | 18.5046 | 0.4339 | 0.3599      | 0.7961     | 0.1455     |
| 4.8644        | 1.4311 | 2500 | 5.0343          | 49.604  | 10.9617  | 42.8337   | 95.0164  | 7.1277 | 18.8397 | 0.4403 | 0.3681      | 0.7991     | 0.1536     |
| 4.8532        | 1.7173 | 3000 | 5.0192          | 49.3028 | 10.3908  | 42.1003   | 95.4172  | 6.9579 | 14.4955 | 0.4389 | 0.3588      | 0.8116     | 0.1462     |
| 4.8343        | 2.0034 | 3500 | 5.0058          | 49.2487 | 11.0341  | 42.1651   | 94.5467  | 7.2777 | 21.4311 | 0.4401 | 0.3693      | 0.7926     | 0.1583     |
| 4.719         | 2.2897 | 4000 | 5.0043          | 49.8632 | 11.2301  | 42.9018   | 95.4578  | 6.5783 | 15.364  | 0.4509 | 0.3735      | 0.8138     | 0.1654     |
| 4.6898        | 2.5759 | 4500 | 4.9904          | 49.9624 | 11.3392  | 43.3503   | 95.1978  | 6.9214 | 18.1433 | 0.449  | 0.3764      | 0.8068     | 0.1637     |
| 4.7061        | 2.8622 | 5000 | 4.9840          | 49.9367 | 11.8606  | 42.6481   | 95.3013  | 6.9934 | 16.9996 | 0.4516 | 0.3748      | 0.8158     | 0.1643     |
| 4.6392        | 3.1483 | 5500 | 4.9898          | 50.5502 | 11.928   | 44.3611   | 95.3614  | 6.9017 | 18.7169 | 0.4523 | 0.3813      | 0.8091     | 0.1665     |
| 4.578         | 3.4345 | 6000 | 4.9893          | 50.39   | 12.0634  | 43.6891   | 95.4175  | 6.8384 | 17.0137 | 0.4567 | 0.3837      | 0.8154     | 0.171      |
| 4.5981        | 3.7208 | 6500 | 4.9843          | 51.0933 | 12.516   | 45.354    | 95.4099  | 6.642  | 19.5688 | 0.4555 | 0.3857      | 0.8046     | 0.1763     |
| 4.5826        | 4.0069 | 7000 | 4.9818          | 50.788  | 12.8273  | 44.4249   | 95.1118  | 6.6555 | 21.2107 | 0.4594 | 0.3942      | 0.8049     | 0.1791     |
| 4.4927        | 4.2931 | 7500 | 5.0009          | 50.4098 | 12.2269  | 43.9055   | 95.0968  | 6.754  | 20.3637 | 0.4602 | 0.3948      | 0.8096     | 0.1763     |
| 4.5009        | 4.5794 | 8000 | 4.9908          | 50.7179 | 12.8769  | 43.783    | 95.4938  | 6.5702 | 17.565  | 0.4601 | 0.3863      | 0.8152     | 0.1787     |
| 4.5128        | 4.8656 | 8500 | 4.9830          | 50.7341 | 12.5935  | 44.2741   | 95.3346  | 6.7056 | 18.9024 | 0.4588 | 0.3905      | 0.8076     | 0.1783     |
| 4.457         | 5.1517 | 9000 | 5.0095          | 50.8947 | 12.7442  | 44.829    | 95.111   | 6.8278 | 21.5163 | 0.462  | 0.3987      | 0.8062     | 0.181      |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.9.1+cu128
- Datasets 3.6.0
- Tokenizers 0.22.1