| | --- |
| | language: |
| | - id |
| | license: apache-2.0 |
| | base_model: LazarusNLP/IndoNanoT5-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - rouge |
| | model-index: |
| | - name: summarization-lora-0 |
| | 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. --> |
| |
|
| | # summarization-lora-0 |
| |
|
| | This model is a fine-tuned version of [LazarusNLP/IndoNanoT5-base](https://huggingface.co/LazarusNLP/IndoNanoT5-base) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.4872 |
| | - Rouge1: 0.4018 |
| | - Rouge2: 0.0 |
| | - Rougel: 0.3958 |
| | - Rougelsum: 0.3983 |
| | - Gen Len: 1.0 |
| |
|
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
| | | 0.7738 | 1.0 | 892 | 0.5310 | 0.704 | 0.0 | 0.6981 | 0.7001 | 1.0 | |
| | | 0.5926 | 2.0 | 1784 | 0.5096 | 0.6968 | 0.0 | 0.6921 | 0.6922 | 1.0 | |
| | | 0.5492 | 3.0 | 2676 | 0.4948 | 0.6619 | 0.0 | 0.659 | 0.6573 | 1.0 | |
| | | 0.5199 | 4.0 | 3568 | 0.4957 | 0.7098 | 0.0 | 0.7065 | 0.7048 | 1.0 | |
| | | 0.4984 | 5.0 | 4460 | 0.4872 | 0.6882 | 0.0 | 0.6851 | 0.6829 | 1.0 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.40.2 |
| | - Pytorch 2.3.1+cu121 |
| | - Datasets 2.20.0 |
| | - Tokenizers 0.19.1 |
| |
|
