gpt2_medium_AR_unigram_65536_parallel3_42
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.2637
- Accuracy: 0.4140
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 |
|---|---|---|---|---|
| 3.7051 | 1.0 | 27788 | 3.6525 | 0.3675 |
| 3.5227 | 2.0 | 55576 | 3.4967 | 0.3826 |
| 3.4257 | 3.0 | 83364 | 3.4212 | 0.3914 |
| 3.3564 | 4.0 | 111152 | 3.3735 | 0.3979 |
| 3.3054 | 5.0 | 138940 | 3.3421 | 0.4013 |
| 3.2555 | 6.0 | 166728 | 3.3173 | 0.4055 |
| 3.2128 | 7.0 | 194516 | 3.2970 | 0.4082 |
| 3.1731 | 8.0 | 222304 | 3.2811 | 0.4106 |
| 3.1322 | 9.0 | 250092 | 3.2692 | 0.4128 |
| 3.0932 | 10.0 | 277880 | 3.2637 | 0.4140 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.8.0+cu128
- Datasets 4.1.1
- Tokenizers 0.19.1
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