| --- |
| 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: 0.6660 |
|
|
| ## 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 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | 3.3723 | 1.0 | 6 | 2.7100 | |
| | 2.3610 | 2.0 | 12 | 1.9674 | |
| | 1.8441 | 3.0 | 18 | 1.6414 | |
| | 1.6440 | 4.0 | 24 | 1.7133 | |
| | 1.6275 | 5.0 | 30 | 1.5587 | |
| | 1.5577 | 6.0 | 36 | 1.4983 | |
| | 1.4918 | 7.0 | 42 | 1.4335 | |
| | 1.4306 | 8.0 | 48 | 1.3870 | |
| | 1.3583 | 9.0 | 54 | 1.5533 | |
| | 1.4316 | 10.0 | 60 | 1.3992 | |
| | 1.3427 | 11.0 | 66 | 1.3620 | |
| | 1.3047 | 12.0 | 72 | 1.2491 | |
| | 1.2281 | 13.0 | 78 | 1.1471 | |
| | 1.1542 | 14.0 | 84 | 1.1002 | |
| | 1.1274 | 15.0 | 90 | 1.3248 | |
| | 1.1864 | 16.0 | 96 | 1.2169 | |
| | 1.1328 | 17.0 | 102 | 1.1488 | |
| | 1.0901 | 18.0 | 108 | 1.0341 | |
| | 1.0214 | 19.0 | 114 | 0.9890 | |
| | 1.0060 | 20.0 | 120 | 1.1041 | |
| | 1.0463 | 21.0 | 126 | 1.0832 | |
| | 1.0114 | 22.0 | 132 | 0.9414 | |
| | 0.9680 | 23.0 | 138 | 1.0066 | |
| | 0.9854 | 24.0 | 144 | 0.9178 | |
| | 0.9139 | 25.0 | 150 | 0.8783 | |
| | 0.9392 | 26.0 | 156 | 0.8476 | |
| | 0.8653 | 27.0 | 162 | 0.8081 | |
| | 0.8270 | 28.0 | 168 | 0.8145 | |
| | 0.8342 | 29.0 | 174 | 0.7931 | |
| | 0.8104 | 30.0 | 180 | 0.7706 | |
| | 0.8007 | 31.0 | 186 | 0.7405 | |
| | 0.7581 | 32.0 | 192 | 0.7223 | |
| | 0.7534 | 33.0 | 198 | 0.7220 | |
| | 0.7468 | 34.0 | 204 | 0.7195 | |
| | 0.7329 | 35.0 | 210 | 0.7129 | |
| | 0.7140 | 36.0 | 216 | 0.6833 | |
| | 0.7118 | 37.0 | 222 | 0.6774 | |
| | 0.7359 | 38.0 | 228 | 0.6700 | |
| | 0.7210 | 39.0 | 234 | 0.6725 | |
| | 0.6968 | 40.0 | 240 | 0.6660 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.0.0 |
| - Pytorch 2.10.0+cpu |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
| |
