| | --- |
| | 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: 0.5921 |
| |
|
| | ## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 40 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:-----:|:----:|:---------------:| |
| | | 3.462 | 1.0 | 5 | 2.8547 | |
| | | 2.538 | 2.0 | 10 | 2.0897 | |
| | | 1.9404 | 3.0 | 15 | 1.7253 | |
| | | 1.7165 | 4.0 | 20 | 1.6144 | |
| | | 1.6205 | 5.0 | 25 | 1.5616 | |
| | | 1.5595 | 6.0 | 30 | 1.5343 | |
| | | 1.533 | 7.0 | 35 | 1.5129 | |
| | | 1.5116 | 8.0 | 40 | 1.4738 | |
| | | 1.47 | 9.0 | 45 | 1.4300 | |
| | | 1.4339 | 10.0 | 50 | 1.4170 | |
| | | 1.4026 | 11.0 | 55 | 1.3703 | |
| | | 1.3849 | 12.0 | 60 | 1.3283 | |
| | | 1.3616 | 13.0 | 65 | 1.2966 | |
| | | 1.3063 | 14.0 | 70 | 1.2537 | |
| | | 1.2479 | 15.0 | 75 | 1.1862 | |
| | | 1.1756 | 16.0 | 80 | 1.1101 | |
| | | 1.1533 | 17.0 | 85 | 1.1242 | |
| | | 1.1344 | 18.0 | 90 | 1.1090 | |
| | | 1.0864 | 19.0 | 95 | 1.0031 | |
| | | 1.0175 | 20.0 | 100 | 0.9584 | |
| | | 0.9662 | 21.0 | 105 | 0.9226 | |
| | | 0.9294 | 22.0 | 110 | 0.8753 | |
| | | 0.8923 | 23.0 | 115 | 0.8596 | |
| | | 0.8676 | 24.0 | 120 | 0.8074 | |
| | | 0.8371 | 25.0 | 125 | 0.7753 | |
| | | 0.8185 | 26.0 | 130 | 0.7829 | |
| | | 0.8092 | 27.0 | 135 | 0.7452 | |
| | | 0.7693 | 28.0 | 140 | 0.7231 | |
| | | 0.7534 | 29.0 | 145 | 0.7025 | |
| | | 0.7432 | 30.0 | 150 | 0.6977 | |
| | | 0.7249 | 31.0 | 155 | 0.6820 | |
| | | 0.7161 | 32.0 | 160 | 0.6609 | |
| | | 0.703 | 33.0 | 165 | 0.6529 | |
| | | 0.6926 | 34.0 | 170 | 0.6395 | |
| | | 0.6771 | 35.0 | 175 | 0.6246 | |
| | | 0.667 | 36.0 | 180 | 0.6204 | |
| | | 0.6633 | 37.0 | 185 | 0.6057 | |
| | | 0.6498 | 38.0 | 190 | 0.6014 | |
| | | 0.642 | 39.0 | 195 | 0.5947 | |
| | | 0.6433 | 40.0 | 200 | 0.5921 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.38.1 |
| | - Pytorch 2.1.0+cu121 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.15.2 |
| |
|
