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calculator_model_test
Agral/calculator_model_test
calculator_model_test is a machine learning model from Agral. 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 4, 2024
- Updated
- Mar 4, 2024
- SHA
- cd004844
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: 0.6006
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 |
|---|---|---|---|
| 3.486 | 1.0 | 5 | 2.9161 |
| 2.5763 | 2.0 | 10 | 2.1493 |
| 1.965 | 3.0 | 15 | 1.7717 |
| 1.6868 | 4.0 | 20 | 1.6013 |
| 1.5787 | 5.0 | 25 | 1.5372 |
| 1.5007 | 6.0 | 30 | 1.4588 |
| 1.428 | 7.0 | 35 | 1.4072 |
| 1.4041 | 8.0 | 40 | 1.3590 |
| 1.3104 | 9.0 | 45 | 1.2594 |
| 1.279 | 10.0 | 50 | 1.2948 |
| 1.2457 | 11.0 | 55 | 1.2035 |
| 1.1598 | 12.0 | 60 | 1.0922 |
| 1.0812 | 13.0 | 65 | 1.0745 |
| 1.0613 | 14.0 | 70 | 1.0448 |
| 1.0542 | 15.0 | 75 | 1.0009 |
| 1.0459 | 16.0 | 80 | 0.9843 |
| 1.0733 | 17.0 | 85 | 1.1919 |
| 1.0664 | 18.0 | 90 | 1.0079 |
| 0.9639 | 19.0 | 95 | 0.9124 |
| 0.9094 | 20.0 | 100 | 0.8717 |
| 0.8693 | 21.0 | 105 | 0.8281 |
| 0.8348 | 22.0 | 110 | 0.7971 |
| 0.8095 | 23.0 | 115 | 0.8027 |
| 0.7985 | 24.0 | 120 | 0.7565 |
| 0.784 | 25.0 | 125 | 0.7354 |
| 0.7934 | 26.0 | 130 | 0.8105 |
| 0.7754 | 27.0 | 135 | 0.7499 |
| 0.7381 | 28.0 | 140 | 0.6967 |
| 0.7124 | 29.0 | 145 | 0.6911 |
| 0.7058 | 30.0 | 150 | 0.6855 |
| 0.6998 | 31.0 | 155 | 0.6779 |
| 0.6966 | 32.0 | 160 | 0.6676 |
| 0.6859 | 33.0 | 165 | 0.6618 |
| 0.6774 | 34.0 | 170 | 0.6418 |
| 0.6617 | 35.0 | 175 | 0.6278 |
| 0.6521 | 36.0 | 180 | 0.6152 |
| 0.6422 | 37.0 | 185 | 0.6121 |
| 0.6358 | 38.0 | 190 | 0.6074 |
| 0.631 | 39.0 | 195 | 0.6022 |
| 0.6294 | 40.0 | 200 | 0.6006 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Library
- transformers
- Type
- encoder-decoder
- Created
- Mar 4, 2024
- Updated
- Mar 4, 2024