File size: 2,207 Bytes
a117781 ad4c781 9763b05 a117781 ad4c781 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 |
---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-base-finetuned-CNN-DailyNews
results: []
pipeline_tag: summarization
datasets:
- cnn_dailymail
---
<!-- 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-CNN-DailyNews
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: 0.9584
- Rouge1: 0.1977
- Rouge2: 0.1321
- Rougel: 0.1792
- Rougelsum: 0.1884
## 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: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.6767 | 1.0 | 63 | 1.8911 | 0.1745 | 0.0915 | 0.1536 | 0.1644 |
| 2.0691 | 2.0 | 126 | 1.5904 | 0.1777 | 0.1003 | 0.1579 | 0.1677 |
| 1.8047 | 3.0 | 189 | 1.3652 | 0.1778 | 0.1029 | 0.1587 | 0.1663 |
| 1.6345 | 4.0 | 252 | 1.2317 | 0.1959 | 0.1226 | 0.1751 | 0.1842 |
| 1.4837 | 5.0 | 315 | 1.1099 | 0.2015 | 0.1265 | 0.1796 | 0.1911 |
| 1.3904 | 6.0 | 378 | 1.0267 | 0.2004 | 0.1278 | 0.1799 | 0.1893 |
| 1.2876 | 7.0 | 441 | 0.9788 | 0.1978 | 0.1307 | 0.1784 | 0.1878 |
| 1.2578 | 8.0 | 504 | 0.9584 | 0.1977 | 0.1321 | 0.1792 | 0.1884 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1 |