---
tags:
- generated_from_trainer
datasets:
- id_liputan6
model-index:
- name: bert2bert-abs-generationconfig-lr-5e-05-encmaxlen-512-decmaxlen-256
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert2bert-abs-generationconfig-lr-5e-05-encmaxlen-512-decmaxlen-256

This model was trained from scratch on the id_liputan6 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4820
- R1 Precision: 0.0734
- R1 Recall: 0.5856
- R1 Fmeasure: 0.1301
- R2 Precision: 0.0268
- R2 Recall: 0.2229
- R2 Fmeasure: 0.0478
- Rl Precision: 0.0524
- Rl Recall: 0.4201
- Rl Fmeasure: 0.0929

## 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: 5e-05
- train_batch_size: 18
- eval_batch_size: 18
- 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 | R1 Precision | R1 Recall | R1 Fmeasure | R2 Precision | R2 Recall | R2 Fmeasure | Rl Precision | Rl Recall | Rl Fmeasure |
|:-------------:|:-----:|:-----:|:---------------:|:------------:|:---------:|:-----------:|:------------:|:---------:|:-----------:|:------------:|:---------:|:-----------:|
| 2.2905        | 1.0   | 10772 | 2.6334          | 0.0695       | 0.5865    | 0.124       | 0.0254       | 0.223     | 0.0454      | 0.0495       | 0.4196    | 0.0883      |
| 1.4553        | 2.0   | 21544 | 2.5229          | 0.0717       | 0.578     | 0.1273      | 0.0258       | 0.2165    | 0.046       | 0.0512       | 0.414     | 0.0908      |
| 1.2405        | 3.0   | 32316 | 2.4820          | 0.0734       | 0.5856    | 0.1301      | 0.0268       | 0.2229    | 0.0478      | 0.0524       | 0.4201    | 0.0929      |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2