gpt2_small_KO_superbpe_49152_parallel10_42
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 5.6888
- Accuracy: 0.2199
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 |
|---|---|---|---|---|
| 8.2544 | 1.0 | 1128 | 7.2983 | 0.1631 |
| 7.0203 | 2.0 | 2256 | 6.5681 | 0.1818 |
| 6.5158 | 3.0 | 3384 | 6.2521 | 0.1931 |
| 6.2434 | 4.0 | 4512 | 6.0507 | 0.2013 |
| 6.0545 | 5.0 | 5640 | 5.9214 | 0.2074 |
| 5.916 | 6.0 | 6768 | 5.8296 | 0.2110 |
| 5.8128 | 7.0 | 7896 | 5.7654 | 0.2151 |
| 5.6712 | 8.0 | 9024 | 5.7241 | 0.2176 |
| 5.6217 | 9.0 | 10152 | 5.6984 | 0.2189 |
| 5.5918 | 10.0 | 11280 | 5.6888 | 0.2199 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.8.0+cu128
- Datasets 4.1.1
- Tokenizers 0.19.1
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