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calculator_model_test
kajama/calculator_model_test
calculator_model_test is a machine learning model from kajama. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- Model type
- encoder-decoder
- Access
- Public
- Created
- Mar 7, 2024
- Updated
- Mar 7, 2024
- SHA
- f6236869
Model card
From the Hugging Face model README
<!-- 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 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7518
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 |
|---|---|---|---|
| 3.392 | 1.0 | 6 | 2.7421 |
| 2.3678 | 2.0 | 12 | 1.9842 |
| 1.8103 | 3.0 | 18 | 1.6702 |
| 1.6444 | 4.0 | 24 | 1.5900 |
| 1.5998 | 5.0 | 30 | 1.5549 |
| 1.6759 | 6.0 | 36 | 1.5762 |
| 1.5344 | 7.0 | 42 | 1.5907 |
| 1.5276 | 8.0 | 48 | 1.5784 |
| 1.5187 | 9.0 | 54 | 1.5224 |
| 1.5007 | 10.0 | 60 | 1.4601 |
| 1.4285 | 11.0 | 66 | 1.4192 |
| 1.3919 | 12.0 | 72 | 1.3792 |
| 1.3663 | 13.0 | 78 | 1.3728 |
| 1.3035 | 14.0 | 84 | 1.2453 |
| 1.2542 | 15.0 | 90 | 1.2191 |
| 1.2343 | 16.0 | 96 | 1.1600 |
| 1.1959 | 17.0 | 102 | 1.1465 |
| 1.1617 | 18.0 | 108 | 1.0958 |
| 1.1189 | 19.0 | 114 | 1.0729 |
| 1.1026 | 20.0 | 120 | 1.1611 |
| 1.1227 | 21.0 | 126 | 1.0368 |
| 1.0386 | 22.0 | 132 | 1.0107 |
| 0.9962 | 23.0 | 138 | 0.9677 |
| 0.9762 | 24.0 | 144 | 0.9360 |
| 0.9474 | 25.0 | 150 | 0.9168 |
| 0.9317 | 26.0 | 156 | 0.9569 |
| 0.9156 | 27.0 | 162 | 0.9376 |
| 0.9061 | 28.0 | 168 | 0.9363 |
| 0.9147 | 29.0 | 174 | 0.9067 |
| 0.9141 | 30.0 | 180 | 0.8845 |
| 0.8753 | 31.0 | 186 | 0.8666 |
| 0.8572 | 32.0 | 192 | 0.8369 |
| 0.848 | 33.0 | 198 | 0.8324 |
| 0.8231 | 34.0 | 204 | 0.7965 |
| 0.8167 | 35.0 | 210 | 0.7844 |
| 0.8004 | 36.0 | 216 | 0.7741 |
| 0.7786 | 37.0 | 222 | 0.7700 |
| 0.8023 | 38.0 | 228 | 0.7571 |
| 0.7799 | 39.0 | 234 | 0.7593 |
| 0.7947 | 40.0 | 240 | 0.7518 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Library
- transformers
- Type
- encoder-decoder
- Created
- Mar 7, 2024
- Updated
- Mar 7, 2024