indobert-base-p2-finetuned-mer
This model is a fine-tuned version of indobenchmark/indobert-base-p2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 4.1964
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: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- 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 |
|---|---|---|---|
| 7.7183 | 1.0 | 28 | 6.6949 |
| 6.3179 | 2.0 | 56 | 5.7267 |
| 5.5857 | 3.0 | 84 | 5.2449 |
| 5.17 | 4.0 | 112 | 4.8586 |
| 4.893 | 5.0 | 140 | 4.6777 |
| 4.7121 | 6.0 | 168 | 4.4832 |
| 4.5402 | 7.0 | 196 | 4.3532 |
| 4.4698 | 8.0 | 224 | 4.2814 |
| 4.4012 | 9.0 | 252 | 4.2612 |
| 4.3725 | 10.0 | 280 | 4.2325 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.2
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