Instructions to use Madan-05/MyGemmaNPC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Madan-05/MyGemmaNPC with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Madan-05/MyGemmaNPC", dtype="auto") - Notebooks
- Google Colab
- Kaggle
MyGemmaNPC
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 5.4883
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: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4.5105 | 1.0 | 5 | 3.8727 |
| 2.7743 | 2.0 | 10 | 3.6730 |
| 1.7911 | 3.0 | 15 | 3.7910 |
| 0.7676 | 4.0 | 20 | 4.6317 |
| 0.4796 | 5.0 | 25 | 5.4883 |
Framework versions
- Transformers 4.55.4
- Pytorch 2.8.0+cu128
- Datasets 2.19.1
- Tokenizers 0.21.4
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