---
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: patchtst-tsmixup
  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. -->

# patchtst-tsmixup

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1553
- Mse: 280.0361
- Mae: 0.6489
- Rmse: 16.7343
- Smape: 100.3318

## 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: 0.0001
- train_batch_size: 256
- eval_batch_size: 512
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 512
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 100

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Mse      | Mae    | Rmse    | Smape    |
|:-------------:|:------:|:-----:|:---------------:|:--------:|:------:|:-------:|:--------:|
| 0.1797        | 0.0952 | 1000  | 0.1756          | 447.3596 | 0.7397 | 21.1509 | 90.8971  |
| 0.1709        | 0.1904 | 2000  | 0.1691          | 425.0924 | 0.7153 | 20.6178 | 112.3049 |
| 0.1722        | 0.2857 | 3000  | 0.1662          | 516.2153 | 0.7009 | 22.7204 | 89.5236  |
| 0.1694        | 0.3809 | 4000  | 0.1643          | 321.2047 | 0.6708 | 17.9222 | 93.0515  |
| 0.1648        | 0.4761 | 5000  | 0.1626          | 350.6870 | 0.6731 | 18.7266 | 94.0748  |
| 0.1672        | 0.5713 | 6000  | 0.1612          | 370.8825 | 0.6797 | 19.2583 | 84.6619  |
| 0.1623        | 0.6666 | 7000  | 0.1605          | 400.0790 | 0.6715 | 20.0020 | 89.7598  |
| 0.1638        | 0.7618 | 8000  | 0.1613          | 387.6971 | 0.6771 | 19.6900 | 122.3799 |
| 0.1609        | 0.8570 | 9000  | 0.1602          | 335.3427 | 0.6603 | 18.3124 | 109.3877 |
| 0.1618        | 0.9522 | 10000 | 0.1592          | 318.1492 | 0.6688 | 17.8367 | 76.3322  |
| 0.1588        | 1.0474 | 11000 | 0.1586          | 345.3675 | 0.6628 | 18.5841 | 94.5032  |
| 0.1601        | 1.1426 | 12000 | 0.1580          | 326.8865 | 0.6540 | 18.0800 | 81.2504  |
| 0.1585        | 1.2379 | 13000 | 0.1575          | 279.7964 | 0.6532 | 16.7271 | 107.6181 |
| 0.1567        | 1.3331 | 14000 | 0.1575          | 328.3490 | 0.6622 | 18.1204 | 91.9899  |
| 0.1592        | 1.4283 | 15000 | 0.1567          | 376.8973 | 0.6523 | 19.4138 | 89.7952  |
| 0.16          | 1.5235 | 16000 | 0.1576          | 327.5271 | 0.6580 | 18.0977 | 105.7316 |
| 0.1586        | 1.6188 | 17000 | 0.1568          | 399.5775 | 0.6602 | 19.9894 | 88.6057  |
| 0.1593        | 1.7140 | 18000 | 0.1565          | 359.5630 | 0.6604 | 18.9621 | 325.5064 |
| 0.1562        | 1.8092 | 19000 | 0.1566          | 281.2739 | 0.6545 | 16.7712 | 80.4528  |
| 0.1601        | 1.9044 | 20000 | 0.1570          | 287.3577 | 0.6543 | 16.9516 | 79.5544  |
| 0.1551        | 1.9997 | 21000 | 0.1561          | 279.2150 | 0.6444 | 16.7097 | 102.6016 |
| 0.1532        | 2.0948 | 22000 | 0.1554          | 282.9574 | 0.6454 | 16.8213 | 85.0121  |
| 0.1564        | 2.1901 | 23000 | 0.1554          | 332.3758 | 0.6485 | 18.2312 | 76.0350  |
| 0.1568        | 2.2853 | 24000 | 0.1551          | 356.0441 | 0.6528 | 18.8691 | 92.2597  |
| 0.1569        | 2.3805 | 25000 | 0.1562          | 333.3135 | 0.6536 | 18.2569 | 180.8556 |
| 0.1569        | 2.4757 | 26000 | 0.1551          | 291.0384 | 0.6491 | 17.0598 | 80.7309  |
| 0.1532        | 2.5710 | 27000 | 0.1553          | 280.0361 | 0.6489 | 16.7343 | 100.3318 |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.7.1+cu126
- Datasets 2.17.1
- Tokenizers 0.21.1