|
--- |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: pegasus-multi_news-summarizer_01 |
|
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. --> |
|
|
|
# pegasus-multi_news-summarizer_01 |
|
|
|
This model is a fine-tuned version of [google/pegasus-multi_news](https://huggingface.co/google/pegasus-multi_news) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.2794 |
|
- Rouge1: 52.1693 |
|
- Rouge2: 34.8989 |
|
- Rougel: 41.2385 |
|
- Rougelsum: 48.4365 |
|
- Gen Len: 98.6433 |
|
|
|
## 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: 1 |
|
- eval_batch_size: 1 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 3 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
|
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:| |
|
| 1.3936 | 1.0 | 16113 | 1.2972 | 51.5747 | 34.2062 | 40.7279 | 47.7783 | 95.0004 | |
|
| 1.3664 | 2.0 | 32226 | 1.2817 | 52.1077 | 34.8189 | 41.1614 | 48.3894 | 100.3265 | |
|
| 1.3002 | 3.0 | 48339 | 1.2794 | 52.1693 | 34.8989 | 41.2385 | 48.4365 | 98.6433 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.12.3 |
|
- Pytorch 1.9.0+cu111 |
|
- Datasets 1.15.1 |
|
- Tokenizers 0.10.3 |
|
|
