---
tags:
- generated_from_trainer
datasets:
- id_liputan6
model-index:
- name: bert2bert-model6-last
  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. -->

# bert2bert-model6-last

This model is a fine-tuned version of [](https://huggingface.co/) on the id_liputan6 dataset.
It achieves the following results on the evaluation set:
- Loss: 7.6361
- R1 Precision: 0.1719
- R1 Recall: 0.0279
- R1 Fmeasure: 0.0432
- R2 Precision: 0.0
- R2 Recall: 0.0
- R2 Fmeasure: 0.0
- Rl Precision: 0.1719
- Rl Recall: 0.0274
- Rl Fmeasure: 0.0428

## 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: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:---------:|:-----------:|:------------:|:---------:|:-----------:|:------------:|:---------:|:-----------:|
| 10.0458       | 1.0   | 4    | 8.3786          | 0.0612       | 0.0567    | 0.0584      | 0.0          | 0.0       | 0.0         | 0.0512       | 0.0468    | 0.0485      |
| 7.6302        | 2.0   | 8    | 8.0384          | 0.087        | 0.1202    | 0.1005      | 0.0          | 0.0       | 0.0         | 0.0583       | 0.08      | 0.0669      |
| 7.2136        | 3.0   | 12   | 7.7980          | 0.0598       | 0.0775    | 0.0677      | 0.0057       | 0.0081    | 0.0067      | 0.0516       | 0.067     | 0.0583      |
| 6.8639        | 4.0   | 16   | 7.8075          | 0.0938       | 0.0107    | 0.0192      | 0.0          | 0.0       | 0.0         | 0.0938       | 0.0105    | 0.0188      |
| 6.3433        | 5.0   | 20   | 7.7948          | 0.0406       | 0.0107    | 0.0168      | 0.0          | 0.0       | 0.0         | 0.0406       | 0.0105    | 0.0166      |
| 6.0891        | 6.0   | 24   | 7.7148          | 0.0469       | 0.0107    | 0.0162      | 0.0          | 0.0       | 0.0         | 0.0469       | 0.0105    | 0.015       |
| 6.0284        | 7.0   | 28   | 7.6611          | 0.1406       | 0.0179    | 0.0256      | 0.0          | 0.0       | 0.0         | 0.1406       | 0.0139    | 0.0219      |
| 5.7972        | 8.0   | 32   | 7.6732          | 0.0646       | 0.025     | 0.0332      | 0.0          | 0.0       | 0.0         | 0.0608       | 0.021     | 0.0293      |
| 5.6802        | 9.0   | 36   | 7.6398          | 0.1823       | 0.0279    | 0.0443      | 0.0          | 0.0       | 0.0         | 0.1719       | 0.0241    | 0.0396      |
| 5.4635        | 10.0  | 40   | 7.6361          | 0.1719       | 0.0279    | 0.0432      | 0.0          | 0.0       | 0.0         | 0.1719       | 0.0274    | 0.0428      |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2