|
--- |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: pegasus-newsroom-headline_writer_57k |
|
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-newsroom-headline_writer_57k |
|
|
|
This model is a fine-tuned version of [google/pegasus-newsroom](https://huggingface.co/google/pegasus-newsroom) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.3599 |
|
- Rouge1: 42.2586 |
|
- Rouge2: 23.2731 |
|
- Rougel: 35.8685 |
|
- Rougelsum: 36.0581 |
|
- Gen Len: 34.3651 |
|
|
|
## 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: 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: 3 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
|
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
|
| 1.5213 | 1.0 | 5670 | 1.4040 | 41.8648 | 22.8205 | 35.3983 | 35.535 | 34.8817 | |
|
| 1.4171 | 2.0 | 11340 | 1.3672 | 42.26 | 23.2611 | 35.8016 | 35.9753 | 34.3492 | |
|
| 1.3722 | 3.0 | 17010 | 1.3599 | 42.2586 | 23.2731 | 35.8685 | 36.0581 | 34.3651 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.23.1 |
|
- Pytorch 1.12.1+cu113 |
|
- Datasets 2.6.0 |
|
- Tokenizers 0.13.1 |
|
|
