distilbert-base-multilingual-cased-on-custom-kural-500
This model is a fine-tuned version of distilbert-base-multilingual-cased on the custom 500 kural dataset. It achieves the following results on the evaluation set:
- Loss: 0.4608
- Accuracy: 0.91
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 25 | 0.2557 | 0.89 |
No log | 2.0 | 50 | 0.5950 | 0.79 |
No log | 3.0 | 75 | 0.1989 | 0.92 |
No log | 4.0 | 100 | 0.4856 | 0.89 |
No log | 5.0 | 125 | 0.4785 | 0.89 |
No log | 6.0 | 150 | 0.4426 | 0.91 |
No log | 7.0 | 175 | 0.4699 | 0.9 |
No log | 8.0 | 200 | 0.4488 | 0.92 |
No log | 9.0 | 225 | 0.4552 | 0.92 |
No log | 10.0 | 250 | 0.4608 | 0.91 |
Framework versions
- Transformers 4.39.2
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2
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