gpt2_small_KO_unigram_49152_parallel10_42
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.6836
- Accuracy: 0.3312
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: 64
- eval_batch_size: 64
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 128
- 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
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 6.9299 | 1.0 | 1322 | 5.6985 | 0.2863 |
| 5.6571 | 2.0 | 2644 | 5.2375 | 0.3026 |
| 5.3024 | 3.0 | 3966 | 5.0402 | 0.3115 |
| 4.9894 | 4.0 | 5288 | 4.9176 | 0.3168 |
| 4.8947 | 5.0 | 6610 | 4.8356 | 0.3224 |
| 4.8201 | 6.0 | 7932 | 4.7752 | 0.3249 |
| 4.7029 | 7.0 | 9254 | 4.7351 | 0.3274 |
| 4.6622 | 8.0 | 10576 | 4.7071 | 0.3295 |
| 4.6305 | 9.0 | 11898 | 4.6909 | 0.3303 |
| 4.5812 | 10.0 | 13220 | 4.6836 | 0.3312 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.8.0+cu128
- Datasets 4.1.1
- Tokenizers 0.19.1
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