---
tags:
- generated_from_trainer
datasets:
- id_liputan6
model-index:
- name: bert2bert-model99-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-model99-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: 2.8701
- R1 Precision: 0.3001
- R1 Recall: 0.34
- R1 Fmeasure: 0.3156
- R2 Precision: 0.121
- R2 Recall: 0.1366
- R2 Fmeasure: 0.1269
- Rl Precision: 0.239
- Rl Recall: 0.2707
- Rl Fmeasure: 0.2513

## 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: 8
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------------:|:---------:|:-----------:|:------------:|:---------:|:-----------:|:------------:|:---------:|:-----------:|
| 2.3429        | 1.0   | 10772 | 2.7616          | 0.29         | 0.3334    | 0.3069      | 0.1175       | 0.1351    | 0.1243      | 0.2329       | 0.2678    | 0.2464      |
| 1.5227        | 2.0   | 21544 | 2.6637          | 0.287        | 0.3356    | 0.3062      | 0.1148       | 0.1338    | 0.1222      | 0.2304       | 0.2693    | 0.2457      |
| 1.3203        | 3.0   | 32316 | 2.6384          | 0.2934       | 0.3387    | 0.3111      | 0.1195       | 0.1377    | 0.1265      | 0.2355       | 0.272     | 0.2498      |
| 1.169         | 4.0   | 43088 | 2.6579          | 0.3004       | 0.3403    | 0.3158      | 0.1228       | 0.139     | 0.129       | 0.2407       | 0.2726    | 0.253       |
| 1.0416        | 5.0   | 53860 | 2.6894          | 0.2963       | 0.3367    | 0.3121      | 0.1202       | 0.1362    | 0.1264      | 0.2367       | 0.2691    | 0.2494      |
| 0.9303        | 6.0   | 64632 | 2.7418          | 0.2986       | 0.3417    | 0.3155      | 0.1213       | 0.1384    | 0.1279      | 0.2385       | 0.2727    | 0.2519      |
| 0.8375        | 7.0   | 75404 | 2.8060          | 0.3009       | 0.3417    | 0.3168      | 0.1223       | 0.1384    | 0.1285      | 0.2402       | 0.2727    | 0.2528      |
| 0.7675        | 8.0   | 86176 | 2.8701          | 0.3001       | 0.34      | 0.3156      | 0.121        | 0.1366    | 0.1269      | 0.239        | 0.2707    | 0.2513      |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1
- Datasets 2.19.0
- Tokenizers 0.19.1