gpt2_small_KO_unigram_32768_parallel10_42
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.5096
- Accuracy: 0.3311
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 |
|---|---|---|---|---|
| 6.7518 | 1.0 | 1371 | 5.4986 | 0.2811 |
| 5.4944 | 2.0 | 2742 | 5.0563 | 0.2996 |
| 4.9611 | 3.0 | 4113 | 4.8606 | 0.3085 |
| 4.8293 | 4.0 | 5484 | 4.7370 | 0.3157 |
| 4.7368 | 5.0 | 6855 | 4.6562 | 0.3204 |
| 4.6015 | 6.0 | 8226 | 4.6012 | 0.3232 |
| 4.5492 | 7.0 | 9597 | 4.5618 | 0.3277 |
| 4.5104 | 8.0 | 10968 | 4.5336 | 0.3284 |
| 4.4434 | 9.0 | 12339 | 4.5170 | 0.3296 |
| 4.4256 | 10.0 | 13710 | 4.5096 | 0.3311 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.8.0+cu128
- Datasets 4.1.1
- Tokenizers 0.19.1
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