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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
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
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: 5.1601
- Sari: 50.8615
- Sari Add: 13.6308
- Sari Keep: 44.3195
- Sari Del: 94.6343
- Fkgl: 6.7741
- Bleu: 25.3408
- D Sari: 0.4652
- D Sari Keep: 0.3942
- D Sari Del: 0.809
- D Sari Add: 0.1924
## 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: 20
- label_smoothing_factor: 0.3
### Training results
| Training Loss | Epoch | Step | Bleu | D Sari | D Sari Add | D Sari Del | D Sari Keep | Fkgl | Validation Loss | Sari | Sari Add | Sari Del | Sari Keep |
|:-------------:|:-------:|:-----:|:-------:|:------:|:----------:|:----------:|:-----------:|:------:|:---------------:|:-------:|:--------:|:--------:|:---------:|
| 5.2573 | 0.7459 | 1000 | 13.9528 | 0.3403 | 0.0 | 0.9948 | 0.0261 | 7.106 | 5.1128 | 48.1497 | 8.6665 | 95.2235 | 40.5591 |
| 4.8677 | 1.4915 | 2000 | 15.9556 | 0.3448 | 0.0 | 0.9947 | 0.0397 | 6.9782 | 5.0729 | 48.9106 | 10.0717 | 95.187 | 41.473 |
| 4.7689 | 2.2372 | 3000 | 15.8936 | 0.3431 | 0.0 | 0.9947 | 0.0344 | 6.9015 | 5.0350 | 49.3306 | 10.7042 | 95.2951 | 41.9925 |
| 4.6608 | 2.9830 | 4000 | 15.8724 | 0.3397 | 0.0 | 0.9949 | 0.0242 | 6.7831 | 5.0289 | 49.8733 | 11.7733 | 95.3954 | 42.4512 |
| 4.5534 | 3.7287 | 5000 | 17.3442 | 0.3431 | 0.0 | 0.9947 | 0.0344 | 6.8518 | 5.0233 | 49.9727 | 11.4246 | 95.2881 | 43.2055 |
| 4.4703 | 4.4744 | 6000 | 5.0376 | 49.9166| 11.9432 | 42.5405 | 95.266 | 6.8747 | 17.1222 | 0.4495 | 0.3716 | 0.8118 | 0.1652 |
| 4.4451 | 5.2200 | 7000 | 5.0560 | 50.1126| 12.2016 | 42.8193 | 95.3169 | 6.7038 | 17.4191 | 0.4507 | 0.3723 | 0.8136 | 0.1663 |
| 4.396 | 5.9659 | 8000 | 5.0326 | 50.7081| 12.7094 | 44.1816 | 95.2332 | 6.6043 | 20.0309 | 0.4599 | 0.3867 | 0.8153 | 0.1778 |
| 4.3371 | 6.7115 | 9000 | 5.0637 | 50.6303| 12.9272 | 43.8282 | 95.1356 | 6.763 | 20.4947 | 0.4587 | 0.3834 | 0.8113 | 0.1814 |
| 4.3014 | 7.4572 | 10000 | 5.0950 | 50.4656| 12.8875 | 43.2239 | 95.2854 | 6.6203 | 18.5182 | 0.4575 | 0.3834 | 0.8113 | 0.1779 |
| 4.2664 | 8.2029 | 11000 | 5.1100 | 50.173 | 12.8216 | 43.0231 | 94.6743 | 6.7837 | 23.116 | 0.4554 | 0.3843 | 0.7992 | 0.1829 |
| 4.2373 | 8.9487 | 12000 | 5.1019 | 50.4108| 13.0119 | 43.6241 | 94.5963 | 6.9084 | 24.2771 | 0.4582 | 0.3914 | 0.7996 | 0.1836 |
| 4.2038 | 9.6944 | 13000 | 5.1239 | 50.4995| 13.3065 | 43.4134 | 94.7785 | 6.742 | 23.2113 | 0.4589 | 0.3859 | 0.8035 | 0.1874 |
| 4.1759 | 10.4401 | 14000 | 5.1491 | 50.4754| 13.0605 | 43.7134 | 94.6524 | 6.8311 | 23.9938 | 0.4583 | 0.3853 | 0.8074 | 0.1821 |
| 4.1618 | 11.1857 | 15000 | 5.1601 | 50.8615| 13.6308 | 44.3195 | 94.6343 | 6.7741 | 25.3408 | 0.4652 | 0.3942 | 0.809 | 0.1924 |
| 4.1347 | 11.9316 | 16000 | 5.1643 | 50.5104| 13.6341 | 43.3236 | 94.5734 | 6.8763 | 24.5365 | 0.4609 | 0.3836 | 0.8046 | 0.1944 |
| 4.1155 | 12.6772 | 17000 | 5.1838 | 50.2122| 13.6879 | 42.6409 | 94.3079 | 6.8788 | 25.6935 | 0.4586 | 0.3886 | 0.7954 | 0.1918 |
| 4.1004 | 13.4229 | 18000 | 5.1975 | 50.3625| 13.5012 | 43.2364 | 94.3499 | 6.8343 | 25.8639 | 0.4609 | 0.3921 | 0.7997 | 0.191 |
| 4.0916 | 14.1686 | 19000 | 5.2197 | 50.2762| 13.5701 | 42.9087 | 94.3498 | 6.6728 | 25.7121 | 0.4623 | 0.3926 | 0.8021 | 0.1921 |
| 4.0773 | 14.9144 | 20000 | 5.2248 | 50.4351| 13.6553 | 43.2455 | 94.4045 | 6.7491 | 25.8344 | 0.4628 | 0.3952 | 0.7992 | 0.1939 |
| 4.0639 | 15.6601 | 21000 | 5.2276 | 49.6913| 13.7193 | 41.6269 | 93.7278 | 7.1849 | 27.3581 | 0.4588 | 0.3911 | 0.7903 | 0.1951 |
| 4.0558 | 16.4057 | 22000 | 5.2378 | 50.309 | 13.6643 | 43.0305 | 94.2322 | 6.691 | 26.5571 | 0.4615 | 0.3913 | 0.7983 | 0.195 |
| 4.0454 | 17.1514 | 23000 | 5.2447 | 49.4843| 13.563 | 41.5506 | 93.3394 | 7.1792 | 28.7607 | 0.4556 | 0.3915 | 0.7817 | 0.1936 |
| 4.0411 | 17.8973 | 24000 | 5.2533 | 50.5396| 13.7453 | 43.538 | 94.3355 | 6.8688 | 26.4366 | 0.4642 | 0.3977 | 0.7999 | 0.1949 |
| 4.0327 | 18.6429 | 25000 | 5.2619 | 49.9081| 13.6194 | 42.1831 | 93.9219 | 6.9129 | 27.2276 | 0.4605 | 0.3929 | 0.793 | 0.1956 |
### Framework versions
- Transformers 4.57.3
- Pytorch 2.9.1+cu128
- Datasets 3.6.0
- Tokenizers 0.22.1
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