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---
base_model: google/pegasus-cnn_dailymail
tags:
- generated_from_trainer
datasets:
- billsum
metrics:
- rouge
model-index:
- name: pegasuscnn-dailymail_billsum_model
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: billsum
type: billsum
config: default
split: ca_test
args: default
metrics:
- name: Rouge1
type: rouge
value: 0.4804
---
<!-- 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. -->
# pegasuscnn-dailymail_billsum_model
This model is a fine-tuned version of [google/pegasus-cnn_dailymail](https://huggingface.co/google/pegasus-cnn_dailymail) on the billsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6747
- Rouge1: 0.4804
- Rouge2: 0.2362
- Rougel: 0.3218
- Rougelsum: 0.3218
- Gen Len: 123.3669
## 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: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------:|
| 2.6227 | 1.0 | 198 | 1.9091 | 0.4289 | 0.1938 | 0.2945 | 0.2947 | 120.1855 |
| 1.9714 | 2.0 | 396 | 1.8147 | 0.4517 | 0.2093 | 0.3059 | 0.3061 | 120.7742 |
| 1.903 | 3.0 | 594 | 1.7646 | 0.4607 | 0.2207 | 0.3098 | 0.3102 | 121.121 |
| 1.7973 | 4.0 | 792 | 1.7362 | 0.4719 | 0.2264 | 0.3179 | 0.3178 | 122.3185 |
| 1.7868 | 5.0 | 990 | 1.7137 | 0.4779 | 0.2314 | 0.3191 | 0.3192 | 123.2379 |
| 1.7457 | 6.0 | 1188 | 1.6958 | 0.4748 | 0.2296 | 0.3171 | 0.317 | 123.2056 |
| 1.6687 | 7.0 | 1386 | 1.6873 | 0.4795 | 0.2352 | 0.3216 | 0.3216 | 123.2702 |
| 1.6751 | 8.0 | 1584 | 1.6806 | 0.4835 | 0.2384 | 0.3248 | 0.3245 | 122.8266 |
| 1.6564 | 9.0 | 1782 | 1.6758 | 0.4814 | 0.2359 | 0.3217 | 0.3216 | 123.2984 |
| 1.6333 | 10.0 | 1980 | 1.6747 | 0.4804 | 0.2362 | 0.3218 | 0.3218 | 123.3669 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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