metadata
base_model: google/pegasus-xsum
tags:
- generated_from_trainer
model-index:
- name: asril-pegasus-xlsum-skripsi
results: []
asril-pegasus-xlsum-skripsi
This model is a fine-tuned version of google/pegasus-xsum on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.6919
Model description
this model is spesifically for indonsesian abstractive news article summarization wich has been fine tuning in more than 48k dataset this model fine-tuned using pegasus model
Intended uses & limitations
More information needed
Training and evaluation data
xlsum/indonesian
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4.5256 | 0.1046 | 1000 | 3.4857 |
| 3.699 | 0.2092 | 2000 | 3.1625 |
| 3.4046 | 0.3138 | 3000 | 2.9968 |
| 3.2456 | 0.4184 | 4000 | 2.8834 |
| 3.126 | 0.5230 | 5000 | 2.8127 |
| 3.055 | 0.6275 | 6000 | 2.7644 |
| 3.005 | 0.7321 | 7000 | 2.7281 |
| 2.9597 | 0.8367 | 8000 | 2.7060 |
| 2.9627 | 0.9413 | 9000 | 2.6919 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.1.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1