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library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: pretrain
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. -->
# pretrain
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: 0.5260
## 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: 5e-05
- train_batch_size: 1024
- eval_batch_size: 1024
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.95) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 156250
- num_epochs: 25
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:-----:|:---------------:|
| 0.4587 | 0.3774 | 500 | 1.7455 |
| 0.3676 | 0.7547 | 1000 | 1.3984 |
| 0.3343 | 1.1321 | 1500 | 1.2729 |
| 0.3118 | 1.5094 | 2000 | 1.1772 |
| 0.2953 | 1.8868 | 2500 | 1.0904 |
| 0.2771 | 2.2642 | 3000 | 1.0169 |
| 0.2605 | 2.6415 | 3500 | 0.9581 |
| 0.2501 | 3.0189 | 4000 | 0.8991 |
| 0.2351 | 3.3962 | 4500 | 0.8535 |
| 0.2245 | 3.7736 | 5000 | 0.8164 |
| 0.2168 | 4.1509 | 5500 | 0.7843 |
| 0.2121 | 4.5283 | 6000 | 0.7684 |
| 0.205 | 4.9057 | 6500 | 0.7447 |
| 0.1999 | 5.2830 | 7000 | 0.7284 |
| 0.196 | 5.6604 | 7500 | 0.7089 |
| 0.1894 | 6.0377 | 8000 | 0.7045 |
| 0.188 | 6.4151 | 8500 | 0.6867 |
| 0.1826 | 6.7925 | 9000 | 0.6750 |
| 0.1821 | 7.1698 | 9500 | 0.6672 |
| 0.1753 | 7.5472 | 10000 | 0.6650 |
| 0.1746 | 7.9245 | 10500 | 0.6485 |
| 0.1714 | 8.3019 | 11000 | 0.6420 |
| 0.1726 | 8.6792 | 11500 | 0.6365 |
| 0.169 | 9.0566 | 12000 | 0.6300 |
| 0.1659 | 9.4340 | 12500 | 0.6244 |
| 0.1653 | 9.8113 | 13000 | 0.6164 |
| 0.1646 | 10.1887 | 13500 | 0.6122 |
| 0.1623 | 10.5660 | 14000 | 0.6070 |
| 0.1629 | 10.9434 | 14500 | 0.6045 |
| 0.1603 | 11.3208 | 15000 | 0.5999 |
| 0.16 | 11.6981 | 15500 | 0.5948 |
| 0.1582 | 12.0755 | 16000 | 0.5898 |
| 0.1565 | 12.4528 | 16500 | 0.5868 |
| 0.1541 | 12.8302 | 17000 | 0.5844 |
| 0.1553 | 13.2075 | 17500 | 0.5798 |
| 0.152 | 13.5849 | 18000 | 0.5791 |
| 0.1536 | 13.9623 | 18500 | 0.5745 |
| 0.1525 | 14.3396 | 19000 | 0.5722 |
| 0.1516 | 14.7170 | 19500 | 0.5718 |
| 0.151 | 15.0943 | 20000 | 0.5675 |
| 0.1502 | 15.4717 | 20500 | 0.5672 |
| 0.1505 | 15.8491 | 21000 | 0.5639 |
| 0.1497 | 16.2264 | 21500 | 0.5607 |
| 0.1495 | 16.6038 | 22000 | 0.5583 |
| 0.1463 | 16.9811 | 22500 | 0.5547 |
| 0.1478 | 17.3585 | 23000 | 0.5556 |
| 0.1468 | 17.7358 | 23500 | 0.5534 |
| 0.1468 | 18.1132 | 24000 | 0.5509 |
| 0.1447 | 18.4906 | 24500 | 0.5480 |
| 0.1451 | 18.8679 | 25000 | 0.5479 |
| 0.1449 | 19.2453 | 25500 | 0.5453 |
| 0.1433 | 19.6226 | 26000 | 0.5449 |
| 0.1434 | 20.0 | 26500 | 0.5423 |
| 0.1434 | 20.3774 | 27000 | 0.5404 |
| 0.1428 | 20.7547 | 27500 | 0.5393 |
| 0.1435 | 21.1321 | 28000 | 0.5391 |
| 0.142 | 21.5094 | 28500 | 0.5371 |
| 0.142 | 21.8868 | 29000 | 0.5342 |
| 0.1418 | 22.2642 | 29500 | 0.5340 |
| 0.1417 | 22.6415 | 30000 | 0.5322 |
| 0.1405 | 23.0189 | 30500 | 0.5309 |
| 0.1412 | 23.3962 | 31000 | 0.5300 |
| 0.1395 | 23.7736 | 31500 | 0.5295 |
| 0.1383 | 24.1509 | 32000 | 0.5289 |
| 0.1373 | 24.5283 | 32500 | 0.5272 |
| 0.139 | 24.9057 | 33000 | 0.5260 |
### Framework versions
- Transformers 4.51.1
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
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