---
base_model: Alfahluzi/bert2bert-model99-last
tags:
- generated_from_trainer
datasets:
- id_liputan6
model-index:
- name: bert2bert-model99-last-Xtreme-Train
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert2bert-model99-last-Xtreme-Train

This model is a fine-tuned version of [Alfahluzi/bert2bert-model99-last](https://huggingface.co/Alfahluzi/bert2bert-model99-last) on the id_liputan6 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8449
- R1 Precision: 0.3481
- R1 Recall: 0.3462
- R1 Fmeasure: 0.3448
- R2 Precision: 0.1475
- R2 Recall: 0.1463
- R2 Fmeasure: 0.1458
- Rl Precision: 0.2761
- Rl Recall: 0.2748
- Rl Fmeasure: 0.2736

## 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: 5
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:---------:|:-----------:|:------------:|:---------:|:-----------:|:------------:|:---------:|:-----------:|
| 2.5931        | 1.0   | 495  | 2.3625          | 0.359        | 0.3516    | 0.3528      | 0.159        | 0.155     | 0.1557      | 0.2876       | 0.2819    | 0.2826      |
| 1.8329        | 2.0   | 990  | 2.4301          | 0.3577       | 0.3489    | 0.3508      | 0.1563       | 0.1517    | 0.1528      | 0.286        | 0.2793    | 0.2806      |
| 1.3237        | 3.0   | 1485 | 2.6019          | 0.3483       | 0.3445    | 0.344       | 0.149        | 0.1468    | 0.1468      | 0.2784       | 0.2755    | 0.275       |
| 0.976         | 4.0   | 1980 | 2.7468          | 0.3509       | 0.3481    | 0.3471      | 0.1501       | 0.1483    | 0.1481      | 0.2784       | 0.2765    | 0.2755      |
| 0.7665        | 5.0   | 2475 | 2.8449          | 0.3481       | 0.3462    | 0.3448      | 0.1475       | 0.1463    | 0.1458      | 0.2761       | 0.2748    | 0.2736      |


### Framework versions

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