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--- |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: PatchTSMixer_Stock_Data |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# PatchTSMixer_Stock_Data |
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This model was trained from scratch on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3020.0154 |
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- Mse: 905.7340 |
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- Mae: 24.4882 |
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- Mape: 0.0316 |
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- Msle: 0.0014 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | Mape | Msle | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|:------:|:------:| |
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| 21551.8505 | 1.0 | 51 | 4541.3184 | 464.5912 | 18.1478 | 0.0230 | 0.0008 | |
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| 17948.9632 | 2.0 | 102 | 3327.9248 | 938.6965 | 24.4246 | 0.0315 | 0.0015 | |
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| 15434.5392 | 3.0 | 153 | 3385.0327 | 682.4795 | 20.8618 | 0.0269 | 0.0011 | |
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| 13608.924 | 4.0 | 204 | 3158.7266 | 917.1122 | 23.9337 | 0.0309 | 0.0015 | |
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| 11935.185 | 5.0 | 255 | 3245.8347 | 712.8546 | 21.4648 | 0.0277 | 0.0011 | |
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| 11173.7426 | 6.0 | 306 | 2985.5256 | 1128.7438 | 27.5807 | 0.0355 | 0.0018 | |
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| 11160.5184 | 7.0 | 357 | 2942.4849 | 1075.2869 | 27.0185 | 0.0348 | 0.0017 | |
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| 10815.6434 | 8.0 | 408 | 2908.7529 | 1069.9177 | 27.0118 | 0.0348 | 0.0017 | |
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| 10287.6066 | 9.0 | 459 | 2995.2012 | 947.1976 | 24.9832 | 0.0322 | 0.0015 | |
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| 10123.2739 | 10.0 | 510 | 3020.0154 | 905.7340 | 24.4882 | 0.0316 | 0.0014 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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