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---
license: mit
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-cnn-finetuned-roundup-32
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-cnn-finetuned-roundup-32
This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2324
- Rouge1: 46.462
- Rouge2: 25.9506
- Rougel: 29.4584
- Rougelsum: 44.1863
- Gen Len: 142.0
## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 32
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log | 1.0 | 132 | 1.3139 | 48.8247 | 29.2173 | 31.7628 | 45.8992 | 142.0 |
| No log | 2.0 | 264 | 1.2287 | 47.9398 | 29.4061 | 30.9133 | 44.9142 | 140.9 |
| No log | 3.0 | 396 | 1.2676 | 49.2743 | 30.4469 | 32.8893 | 46.6208 | 142.0 |
| 0.9578 | 4.0 | 528 | 1.3218 | 47.315 | 26.7303 | 30.5007 | 44.7654 | 142.0 |
| 0.9578 | 5.0 | 660 | 1.3173 | 47.1476 | 25.9408 | 29.4257 | 44.4956 | 142.0 |
| 0.9578 | 6.0 | 792 | 1.4283 | 47.5836 | 27.1572 | 29.8553 | 44.8858 | 142.0 |
| 0.9578 | 7.0 | 924 | 1.5005 | 46.6839 | 26.2214 | 30.1895 | 43.8753 | 140.75 |
| 0.3306 | 8.0 | 1056 | 1.5316 | 47.7611 | 27.1105 | 30.8142 | 44.7598 | 142.0 |
| 0.3306 | 9.0 | 1188 | 1.6295 | 48.4416 | 27.6912 | 30.3409 | 45.317 | 142.0 |
| 0.3306 | 10.0 | 1320 | 1.6564 | 46.5751 | 27.2306 | 29.7265 | 43.7327 | 142.0 |
| 0.3306 | 11.0 | 1452 | 1.7471 | 47.9684 | 27.5739 | 30.7018 | 44.6852 | 141.75 |
| 0.145 | 12.0 | 1584 | 1.7700 | 47.9274 | 28.5129 | 31.129 | 45.1009 | 142.0 |
| 0.145 | 13.0 | 1716 | 1.8391 | 49.8091 | 30.1597 | 33.6004 | 47.2007 | 141.95 |
| 0.145 | 14.0 | 1848 | 1.9212 | 45.2195 | 25.033 | 27.4181 | 42.6161 | 142.0 |
| 0.145 | 15.0 | 1980 | 1.9267 | 48.4959 | 28.1 | 31.2796 | 46.2758 | 142.0 |
| 0.0723 | 16.0 | 2112 | 1.9130 | 47.0765 | 27.4929 | 30.6862 | 44.1458 | 142.0 |
| 0.0723 | 17.0 | 2244 | 1.9514 | 48.5354 | 28.4909 | 31.8966 | 45.7116 | 142.0 |
| 0.0723 | 18.0 | 2376 | 2.0064 | 47.9339 | 28.6862 | 32.4472 | 45.3704 | 142.0 |
| 0.042 | 19.0 | 2508 | 2.0210 | 48.3169 | 28.1579 | 30.2681 | 45.3831 | 141.3 |
| 0.042 | 20.0 | 2640 | 2.0377 | 46.8156 | 26.0122 | 28.817 | 43.9383 | 142.0 |
| 0.042 | 21.0 | 2772 | 2.0587 | 46.3813 | 27.3555 | 29.875 | 43.6605 | 142.0 |
| 0.042 | 22.0 | 2904 | 2.0695 | 45.6728 | 26.0639 | 29.5653 | 42.3772 | 142.0 |
| 0.025 | 23.0 | 3036 | 2.1617 | 46.7283 | 26.2082 | 28.52 | 43.3304 | 142.0 |
| 0.025 | 24.0 | 3168 | 2.1375 | 48.1347 | 28.3444 | 31.7509 | 45.4907 | 142.0 |
| 0.025 | 25.0 | 3300 | 2.1911 | 47.3358 | 27.1479 | 29.4923 | 44.0087 | 142.0 |
| 0.025 | 26.0 | 3432 | 2.1806 | 47.2218 | 26.8421 | 30.03 | 44.2417 | 142.0 |
| 0.0153 | 27.0 | 3564 | 2.1890 | 46.3745 | 27.0095 | 29.7274 | 43.3372 | 142.0 |
| 0.0153 | 28.0 | 3696 | 2.2235 | 50.1274 | 30.8817 | 32.8766 | 46.7486 | 141.5 |
| 0.0153 | 29.0 | 3828 | 2.2236 | 50.1785 | 30.8079 | 32.8886 | 46.9888 | 142.0 |
| 0.0153 | 30.0 | 3960 | 2.2312 | 46.7468 | 26.4272 | 30.1175 | 43.9132 | 142.0 |
| 0.0096 | 31.0 | 4092 | 2.2287 | 47.558 | 26.3933 | 29.9122 | 44.5752 | 142.0 |
| 0.0096 | 32.0 | 4224 | 2.2324 | 46.462 | 25.9506 | 29.4584 | 44.1863 | 142.0 |
### Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1
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