generated_from_trainer id base_model:LazarusNLP/IndoNanoT5-base base_model:finetune:LazarusNLP/IndoNanoT5-base license:apache-2.0 region:us
---
base_model: LazarusNLP/IndoNanoT5-base
language:
- id
license: apache-2.0
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: summarization-pt-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-pt-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: 1.3436
- Rouge1: 0.3954
- Rouge2: 0.0
- Rougel: 0.3954
- Rougelsum: 0.3942
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 3.0294        | 1.0   | 892  | 1.9919          | 0.672  | 0.0    | 0.6729 | 0.6683    | 1.0     |
| 2.4162        | 2.0   | 1784 | 1.7555          | 0.7269 | 0.0    | 0.7253 | 0.727     | 1.0     |
| 2.1684        | 3.0   | 2676 | 1.5470          | 0.693  | 0.0    | 0.6917 | 0.6933    | 1.0     |
| 1.9893        | 4.0   | 3568 | 1.4300          | 0.6992 | 0.0    | 0.6959 | 0.6968    | 1.0     |
| 1.8466        | 5.0   | 4460 | 1.3436          | 0.6802 | 0.0    | 0.6802 | 0.6778    | 1.0     |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
