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---
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: patchtst-tsmixup-relu
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-relu
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: 0.1485
- Mse: 229.0122
- Mae: 0.6126
- Rmse: 15.1332
- Smape: 83.2157
## 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: 448
- eval_batch_size: 896
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 896
- 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | Rmse | Smape |
|:-------------:|:------:|:-----:|:---------------:|:--------:|:------:|:-------:|:--------:|
| 0.1785 | 0.1666 | 1000 | 0.1739 | 433.0006 | 0.7291 | 20.8087 | 100.7767 |
| 0.1655 | 0.3333 | 2000 | 0.1654 | 424.8635 | 0.7099 | 20.6122 | 74.2051 |
| 0.1663 | 0.4999 | 3000 | 0.1624 | 381.5935 | 0.6823 | 19.5344 | 142.9640 |
| 0.1632 | 0.6666 | 4000 | 0.1599 | 330.2523 | 0.6648 | 18.1728 | 78.8419 |
| 0.162 | 0.8332 | 5000 | 0.1592 | 322.0357 | 0.6595 | 17.9454 | 78.0993 |
| 0.1615 | 0.9998 | 6000 | 0.1581 | 294.6714 | 0.6549 | 17.1660 | 79.6810 |
| 0.162 | 1.1665 | 7000 | 0.1573 | 333.3479 | 0.6496 | 18.2578 | 81.2097 |
| 0.1587 | 1.3331 | 8000 | 0.1570 | 263.9417 | 0.6429 | 16.2463 | 90.2972 |
| 0.154 | 1.4998 | 9000 | 0.1565 | 268.0528 | 0.6515 | 16.3723 | 83.8961 |
| 0.1562 | 1.6664 | 10000 | 0.1561 | 287.6087 | 0.6475 | 16.9590 | 108.2025 |
| 0.1603 | 1.8330 | 11000 | 0.1558 | 281.4109 | 0.6507 | 16.7753 | 77.4054 |
| 0.1557 | 1.9997 | 12000 | 0.1550 | 281.4917 | 0.6408 | 16.7777 | 81.8113 |
| 0.1568 | 2.1663 | 13000 | 0.1546 | 258.6138 | 0.6406 | 16.0815 | 89.9780 |
| 0.1556 | 2.3329 | 14000 | 0.1545 | 268.3961 | 0.6425 | 16.3828 | 79.0450 |
| 0.1561 | 2.4996 | 15000 | 0.1538 | 249.9753 | 0.6366 | 15.8106 | 88.3079 |
| 0.1546 | 2.6662 | 16000 | 0.1535 | 239.0104 | 0.6313 | 15.4600 | 96.2489 |
| 0.1536 | 2.8329 | 17000 | 0.1534 | 232.7196 | 0.6318 | 15.2552 | 73.1808 |
| 0.1531 | 2.9995 | 18000 | 0.1537 | 224.2394 | 0.6249 | 14.9746 | 99.7205 |
| 0.1535 | 3.1661 | 19000 | 0.1530 | 253.5844 | 0.6296 | 15.9243 | 80.0392 |
| 0.1532 | 3.3328 | 20000 | 0.1529 | 256.6078 | 0.6314 | 16.0190 | 184.8716 |
| 0.1566 | 3.4994 | 21000 | 0.1531 | 228.1704 | 0.6266 | 15.1053 | 90.5678 |
| 0.1547 | 3.6661 | 22000 | 0.1527 | 216.8113 | 0.6265 | 14.7245 | 88.1824 |
| 0.1537 | 3.8327 | 23000 | 0.1522 | 241.5133 | 0.6282 | 15.5407 | 73.5045 |
| 0.1531 | 3.9993 | 24000 | 0.1521 | 232.2086 | 0.6302 | 15.2384 | 87.4450 |
| 0.1525 | 4.1660 | 25000 | 0.1523 | 253.6224 | 0.6328 | 15.9255 | 88.9352 |
| 0.1525 | 4.3326 | 26000 | 0.1517 | 254.2605 | 0.6304 | 15.9455 | 77.5196 |
| 0.1548 | 4.4993 | 27000 | 0.1519 | 225.7644 | 0.6212 | 15.0255 | 82.3784 |
| 0.1527 | 4.6659 | 28000 | 0.1519 | 220.0219 | 0.6254 | 14.8331 | 86.0485 |
| 0.153 | 4.8325 | 29000 | 0.1515 | 258.0009 | 0.6347 | 16.0624 | 145.4315 |
| 0.1521 | 4.9992 | 30000 | 0.1516 | 227.8417 | 0.6227 | 15.0944 | 76.3474 |
| 0.151 | 5.1658 | 31000 | 0.1514 | 213.8730 | 0.6185 | 14.6244 | 157.4075 |
| 0.1527 | 5.3324 | 32000 | 0.1510 | 238.2835 | 0.6189 | 15.4364 | 571.1568 |
| 0.1529 | 5.4991 | 33000 | 0.1510 | 270.1301 | 0.6278 | 16.4356 | 83.5608 |
| 0.1505 | 5.6657 | 34000 | 0.1511 | 241.0177 | 0.6271 | 15.5247 | 76.5107 |
| 0.1521 | 5.8324 | 35000 | 0.1516 | 255.7361 | 0.6331 | 15.9918 | 108.9967 |
| 0.1513 | 5.9990 | 36000 | 0.1507 | 253.1635 | 0.6233 | 15.9111 | 85.8247 |
| 0.1502 | 6.1656 | 37000 | 0.1509 | 255.3432 | 0.6230 | 15.9795 | 118.9721 |
| 0.1517 | 6.3323 | 38000 | 0.1504 | 238.2068 | 0.6213 | 15.4339 | 79.4896 |
| 0.151 | 6.4989 | 39000 | 0.1508 | 244.4908 | 0.6243 | 15.6362 | 98.8420 |
| 0.1516 | 6.6656 | 40000 | 0.1504 | 229.2746 | 0.6231 | 15.1418 | 71.1164 |
| 0.1506 | 6.8322 | 41000 | 0.1501 | 237.0237 | 0.6217 | 15.3956 | 74.7138 |
| 0.1503 | 6.9988 | 42000 | 0.1500 | 240.7731 | 0.6206 | 15.5169 | 85.3629 |
| 0.1493 | 7.1655 | 43000 | 0.1501 | 265.2171 | 0.6242 | 16.2855 | 157.2147 |
| 0.1501 | 7.3321 | 44000 | 0.1499 | 247.8091 | 0.6219 | 15.7420 | 98.6004 |
| 0.1508 | 7.4988 | 45000 | 0.1497 | 265.8900 | 0.6227 | 16.3061 | 72.4383 |
| 0.1518 | 7.6654 | 46000 | 0.1497 | 249.7165 | 0.6216 | 15.8024 | 110.3652 |
| 0.1502 | 7.8320 | 47000 | 0.1496 | 248.1616 | 0.6200 | 15.7531 | 77.3612 |
| 0.1503 | 7.9987 | 48000 | 0.1493 | 237.9707 | 0.6190 | 15.4263 | 71.8934 |
| 0.1502 | 8.1653 | 49000 | 0.1494 | 225.7567 | 0.6149 | 15.0252 | 78.6202 |
| 0.1492 | 8.3319 | 50000 | 0.1492 | 258.1519 | 0.6185 | 16.0671 | 73.3061 |
| 0.1513 | 8.4986 | 51000 | 0.1491 | 226.3746 | 0.6162 | 15.0458 | 118.5835 |
| 0.1508 | 8.6652 | 52000 | 0.1491 | 236.9618 | 0.6171 | 15.3936 | 80.4855 |
| 0.1517 | 8.8319 | 53000 | 0.1490 | 242.2040 | 0.6186 | 15.5629 | 144.8560 |
| 0.1494 | 8.9985 | 54000 | 0.1490 | 237.0488 | 0.6174 | 15.3964 | 78.5948 |
| 0.1477 | 9.1651 | 55000 | 0.1488 | 232.7170 | 0.6157 | 15.2551 | 82.3074 |
| 0.1499 | 9.3318 | 56000 | 0.1488 | 236.9111 | 0.6168 | 15.3919 | 77.6623 |
| 0.1524 | 9.4984 | 57000 | 0.1487 | 231.8599 | 0.6148 | 15.2269 | 102.9215 |
| 0.1505 | 9.6651 | 58000 | 0.1486 | 230.8095 | 0.6139 | 15.1924 | 67.3176 |
| 0.1507 | 9.8317 | 59000 | 0.1485 | 231.5027 | 0.6137 | 15.2152 | 84.0686 |
| 0.1461 | 9.9983 | 60000 | 0.1485 | 229.0122 | 0.6126 | 15.1332 | 83.2157 |
### Framework versions
- Transformers 4.51.3
- Pytorch 2.7.1+cu126
- Datasets 2.17.1
- Tokenizers 0.21.1
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