metadata
tags:
- generated_from_trainer
datasets:
- liputan6
model-index:
- name: IndoRetNet-Liputan6
results: []
license: apache-2.0
language:
- id
IndoRetNet-Liputan6
This model is a Indonesian RetNet model train using the Liputan6 dataset. Using Tokenizer from IndoBERT It achieves the following results on the evaluation set:
- Loss: 3.4936
Model description
Demonstrate training and recurrent inference using a retentive network (https://arxiv.org/pdf/2307.08621.pdf). The code utilizes Sehyun Choi's implementation of retentive network (https://github.com/syncdoth/RetNet).
- License: Apache 2.0.
Intended uses & limitations
Intended to demonstrate training and (recurrent O(1)) inference using a retentive network in Indonesian language.
Training and evaluation data
Using Train and validation set from Liputan6 dataset provided by NusaCrowd.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0006
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 3.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4.5053 | 0.17 | 1000 | 4.5145 |
| 4.1281 | 0.34 | 2000 | 4.1702 |
| 3.9452 | 0.52 | 3000 | 4.0094 |
| 3.8302 | 0.69 | 4000 | 3.8972 |
| 3.6955 | 0.86 | 5000 | 3.8144 |
| 3.589 | 1.03 | 6000 | 3.7600 |
| 3.5279 | 1.21 | 7000 | 3.7088 |
| 3.4598 | 1.38 | 8000 | 3.6670 |
| 3.4445 | 1.55 | 9000 | 3.6259 |
| 3.4098 | 1.72 | 10000 | 3.5904 |
| 3.3455 | 1.9 | 11000 | 3.5610 |
| 3.2306 | 2.07 | 12000 | 3.5406 |
| 3.261 | 2.24 | 13000 | 3.5216 |
| 3.2204 | 2.41 | 14000 | 3.5111 |
| 3.2321 | 2.59 | 15000 | 3.5001 |
| 3.2514 | 2.76 | 16000 | 3.4941 |
| 3.233 | 2.93 | 17000 | 3.4936 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0