gpt2_medium_ZH_unigram_65536_parallel3-100_42
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.7483
- Accuracy: 0.2951
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 |
|---|---|---|---|---|
| 5.8555 | 1.0 | 5143 | 5.6970 | 0.2315 |
| 5.2895 | 2.0 | 10286 | 5.2078 | 0.2572 |
| 5.032 | 3.0 | 15429 | 5.0051 | 0.2703 |
| 4.8589 | 4.0 | 20572 | 4.8967 | 0.2792 |
| 4.7275 | 5.0 | 25715 | 4.8347 | 0.2841 |
| 4.6171 | 6.0 | 30858 | 4.7934 | 0.2885 |
| 4.5244 | 7.0 | 36001 | 4.7698 | 0.2911 |
| 4.4428 | 8.0 | 41144 | 4.7551 | 0.2934 |
| 4.3695 | 9.0 | 46287 | 4.7490 | 0.2944 |
| 4.3116 | 10.0 | 51430 | 4.7483 | 0.2951 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.8.0+cu128
- Datasets 4.1.1
- Tokenizers 0.19.1
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