| --- |
| library_name: transformers |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: calculator_model_test |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # calculator_model_test |
|
|
| This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1301 |
|
|
| ## 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: 0.001 |
| - train_batch_size: 512 |
| - eval_batch_size: 512 |
| - 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: linear |
| - num_epochs: 40 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | 3.1429 | 1.0 | 4 | 2.2337 | |
| | 2.0240 | 2.0 | 8 | 1.7621 | |
| | 1.6595 | 3.0 | 12 | 1.4806 | |
| | 1.3784 | 4.0 | 16 | 1.1427 | |
| | 1.0363 | 5.0 | 20 | 0.8139 | |
| | 0.7381 | 6.0 | 24 | 0.6046 | |
| | 0.5807 | 7.0 | 28 | 0.5287 | |
| | 0.5117 | 8.0 | 32 | 0.4774 | |
| | 0.4641 | 9.0 | 36 | 0.4449 | |
| | 0.4274 | 10.0 | 40 | 0.4155 | |
| | 0.3970 | 11.0 | 44 | 0.3787 | |
| | 0.3664 | 12.0 | 48 | 0.3443 | |
| | 0.3391 | 13.0 | 52 | 0.3224 | |
| | 0.3196 | 14.0 | 56 | 0.3062 | |
| | 0.3033 | 15.0 | 60 | 0.2950 | |
| | 0.2938 | 16.0 | 64 | 0.2804 | |
| | 0.2757 | 17.0 | 68 | 0.2682 | |
| | 0.2641 | 18.0 | 72 | 0.2580 | |
| | 0.2551 | 19.0 | 76 | 0.2474 | |
| | 0.2441 | 20.0 | 80 | 0.2430 | |
| | 0.2358 | 21.0 | 84 | 0.2323 | |
| | 0.2284 | 22.0 | 88 | 0.2258 | |
| | 0.2149 | 23.0 | 92 | 0.2129 | |
| | 0.2098 | 24.0 | 96 | 0.2078 | |
| | 0.2005 | 25.0 | 100 | 0.1975 | |
| | 0.1898 | 26.0 | 104 | 0.1901 | |
| | 0.1845 | 27.0 | 108 | 0.1790 | |
| | 0.1771 | 28.0 | 112 | 0.1746 | |
| | 0.1708 | 29.0 | 116 | 0.1668 | |
| | 0.1657 | 30.0 | 120 | 0.1610 | |
| | 0.1600 | 31.0 | 124 | 0.1581 | |
| | 0.1559 | 32.0 | 128 | 0.1510 | |
| | 0.1498 | 33.0 | 132 | 0.1475 | |
| | 0.1451 | 34.0 | 136 | 0.1432 | |
| | 0.1426 | 35.0 | 140 | 0.1417 | |
| | 0.1373 | 36.0 | 144 | 0.1365 | |
| | 0.1334 | 37.0 | 148 | 0.1345 | |
| | 0.1335 | 38.0 | 152 | 0.1318 | |
| | 0.1309 | 39.0 | 156 | 0.1303 | |
| | 0.1308 | 40.0 | 160 | 0.1301 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.0.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
| |
