IndoT5 Machine Translation
Collection
Fine-tuned mT5 models on languages of Indonesia. Based on Many-to-Many Multilingual Translation Model for Languages of Indonesia (Wongso et al., 2023)
•
4 items
•
Updated
indo-t5-base-v2
This model is a fine-tuned version of google/mt5-base on the lazarus-project/alkitab-sabda-mt dataset. It achieves the following results on the evaluation set:
- Loss: 1.5099
- Bleu: 15.1824
- Gen Len: 56.1138
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: 0.0008
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 16
- total_train_batch_size: 4096
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 10000
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| 1.3756 | 1.56 | 5000 | 1.5355 | 2.3992 | 18.9403 |
| 1.1295 | 3.11 | 10000 | 1.5099 | 2.543 | 18.9389 |
Framework versions
- Transformers 4.27.1
- Pytorch 2.0.0+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2
- Downloads last month
- 23
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.