22_09_07_walser_blocks_larger_fp16_5ep
This model is a fine-tuned version of stefan-it/german-gpt2-larger on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.1738
- Accuracy: 0.2760
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.45 | 50 | 5.2435 | 0.1883 |
| No log | 0.91 | 100 | 4.6670 | 0.2259 |
| No log | 1.36 | 150 | 4.4367 | 0.2481 |
| No log | 1.82 | 200 | 4.3258 | 0.2597 |
| 6.175 | 2.27 | 250 | 4.2705 | 0.2648 |
| 6.175 | 2.73 | 300 | 4.2318 | 0.2697 |
| 6.175 | 3.18 | 350 | 4.2090 | 0.2719 |
| 6.175 | 3.64 | 400 | 4.1915 | 0.2740 |
| 6.175 | 4.09 | 450 | 4.1823 | 0.2746 |
| 3.9191 | 4.55 | 500 | 4.1761 | 0.2757 |
| 3.9191 | 5.0 | 550 | 4.1738 | 0.2760 |
Framework versions
- Transformers 4.22.0.dev0
- Pytorch 1.11.0.post202
- Datasets 2.3.2
- Tokenizers 0.12.1
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