gpt2_medium_AR_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: 3.6582
- Accuracy: 0.3702
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 |
|---|---|---|---|---|
| 4.3338 | 1.0 | 7033 | 4.2226 | 0.3165 |
| 4.0117 | 2.0 | 14066 | 3.9488 | 0.3387 |
| 3.8486 | 3.0 | 21099 | 3.8274 | 0.3500 |
| 3.7324 | 4.0 | 28132 | 3.7606 | 0.3559 |
| 3.6402 | 5.0 | 35165 | 3.7169 | 0.3610 |
| 3.5599 | 6.0 | 42198 | 3.6898 | 0.3642 |
| 3.4913 | 7.0 | 49231 | 3.6739 | 0.3664 |
| 3.4257 | 8.0 | 56264 | 3.6639 | 0.3684 |
| 3.367 | 9.0 | 63297 | 3.6596 | 0.3700 |
| 3.3164 | 10.0 | 70330 | 3.6582 | 0.3702 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.8.0+cu128
- Datasets 4.1.1
- Tokenizers 0.19.1
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