| --- |
| 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: 0.4101 |
|
|
| ## 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 | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | 1.9065 | 1.0 | 5 | 1.4456 | |
| | 1.4155 | 2.0 | 10 | 1.2758 | |
| | 1.2760 | 3.0 | 15 | 1.1750 | |
| | 1.1812 | 4.0 | 20 | 1.1125 | |
| | 1.1029 | 5.0 | 25 | 1.0135 | |
| | 1.0238 | 6.0 | 30 | 0.9452 | |
| | 0.9754 | 7.0 | 35 | 1.0039 | |
| | 1.0038 | 8.0 | 40 | 0.8954 | |
| | 0.9197 | 9.0 | 45 | 0.8593 | |
| | 0.9007 | 10.0 | 50 | 0.8470 | |
| | 0.8615 | 11.0 | 55 | 0.8050 | |
| | 0.8225 | 12.0 | 60 | 0.7646 | |
| | 0.7921 | 13.0 | 65 | 0.7265 | |
| | 0.7955 | 14.0 | 70 | 0.7123 | |
| | 0.7526 | 15.0 | 75 | 0.6853 | |
| | 0.7354 | 16.0 | 80 | 0.6793 | |
| | 0.7253 | 17.0 | 85 | 0.6548 | |
| | 0.7005 | 18.0 | 90 | 0.6337 | |
| | 0.6761 | 19.0 | 95 | 0.6158 | |
| | 0.6566 | 20.0 | 100 | 0.5916 | |
| | 0.6642 | 21.0 | 105 | 0.5759 | |
| | 0.6408 | 22.0 | 110 | 0.5735 | |
| | 0.6353 | 23.0 | 115 | 0.5868 | |
| | 0.6286 | 24.0 | 120 | 0.5503 | |
| | 0.6109 | 25.0 | 125 | 0.5538 | |
| | 0.6068 | 26.0 | 130 | 0.5321 | |
| | 0.5774 | 27.0 | 135 | 0.5221 | |
| | 0.5733 | 28.0 | 140 | 0.5113 | |
| | 0.5716 | 29.0 | 145 | 0.5014 | |
| | 0.5593 | 30.0 | 150 | 0.4884 | |
| | 0.5554 | 31.0 | 155 | 0.4771 | |
| | 0.5422 | 32.0 | 160 | 0.4739 | |
| | 0.5319 | 33.0 | 165 | 0.4565 | |
| | 0.5182 | 34.0 | 170 | 0.4458 | |
| | 0.5100 | 35.0 | 175 | 0.4406 | |
| | 0.5040 | 36.0 | 180 | 0.4282 | |
| | 0.4940 | 37.0 | 185 | 0.4242 | |
| | 0.4867 | 38.0 | 190 | 0.4195 | |
| | 0.4910 | 39.0 | 195 | 0.4116 | |
| | 0.4794 | 40.0 | 200 | 0.4101 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.0.0 |
| - Pytorch 2.10.0+cpu |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
| |
