|
--- |
|
language: |
|
- id |
|
license: apache-2.0 |
|
base_model: LazarusNLP/IndoNanoT5-base |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- id_liputan6 |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: liputan6-unipelt |
|
results: |
|
- task: |
|
name: Summarization |
|
type: summarization |
|
dataset: |
|
name: id_liputan6 canonical |
|
type: id_liputan6 |
|
config: canonical |
|
split: validation |
|
args: canonical |
|
metrics: |
|
- name: Rouge1 |
|
type: rouge |
|
value: 1.8031 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# liputan6-unipelt |
|
|
|
This model is a fine-tuned version of [LazarusNLP/IndoNanoT5-base](https://huggingface.co/LazarusNLP/IndoNanoT5-base) on the id_liputan6 canonical dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.5645 |
|
- Rouge1: 1.8031 |
|
- Rouge2: 0.4028 |
|
- Rougel: 1.5585 |
|
- Rougelsum: 1.6132 |
|
- Gen Len: 127.0 |
|
|
|
## 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: 0.001 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 5.0 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
|
| 3.9747 | 1.0 | 63 | 3.1043 | 3.9543 | 1.0191 | 3.7375 | 3.7922 | 127.0 | |
|
| 3.0262 | 2.0 | 126 | 2.7314 | 5.0276 | 1.3105 | 4.1292 | 4.3574 | 127.0 | |
|
| 2.6214 | 3.0 | 189 | 2.5645 | 5.2587 | 1.2673 | 3.8487 | 4.3728 | 127.0 | |
|
| 2.3496 | 4.0 | 252 | 2.4158 | 4.4309 | 0.9142 | 3.2152 | 3.5296 | 127.0 | |
|
| 2.1749 | 5.0 | 315 | 2.3672 | 5.0669 | 1.0704 | 3.6335 | 4.1011 | 127.0 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.40.2 |
|
- Pytorch 2.3.1+cu121 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
|
|
