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pretrain_2
Thalesian/pretrain_2
pretrain_2 is a machine learning model from Thalesian. 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
- t5
- Access
- Public
- Created
- Dec 9, 2024
- Updated
- Dec 9, 2024
- SHA
- 523685c6
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. -->
pretrain_2
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5716
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: 48
- eval_batch_size: 48
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 96
- total_eval_batch_size: 96
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 200
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.7609 | 1.0 | 24286 | 0.6893 |
| 0.7239 | 2.0 | 48572 | 0.6476 |
| 0.7056 | 3.0 | 72858 | 0.6279 |
| 0.6961 | 4.0 | 97144 | 0.6242 |
| 0.6838 | 5.0 | 121430 | 0.6123 |
| 0.6742 | 6.0 | 145716 | 0.6111 |
| 0.6762 | 7.0 | 170002 | 0.6064 |
| 0.6722 | 8.0 | 194288 | 0.6052 |
| 0.6603 | 9.0 | 218574 | 0.6043 |
| 0.6522 | 10.0 | 242860 | 0.6005 |
| 0.654 | 11.0 | 267146 | 0.6022 |
| 0.6422 | 12.0 | 291432 | 0.5964 |
| 0.6495 | 13.0 | 315718 | 0.5967 |
| 0.655 | 14.0 | 340004 | 0.5961 |
| 0.651 | 15.0 | 364290 | 0.5925 |
| 0.6458 | 16.0 | 388576 | 0.5922 |
| 0.6441 | 17.0 | 412862 | 0.5901 |
| 0.6477 | 18.0 | 437148 | 0.5871 |
| 0.6382 | 19.0 | 461434 | 0.5896 |
| 0.6426 | 20.0 | 485720 | 0.5878 |
| 0.6369 | 21.0 | 510006 | 0.5873 |
| 0.6298 | 22.0 | 534292 | 0.5844 |
| 0.6388 | 23.0 | 558578 | 0.5863 |
| 0.6389 | 24.0 | 582864 | 0.5826 |
| 0.6394 | 25.0 | 607150 | 0.5861 |
| 0.6295 | 26.0 | 631436 | 0.5848 |
| 0.6365 | 27.0 | 655722 | 0.5815 |
| 0.6347 | 28.0 | 680008 | 0.5836 |
| 0.6384 | 29.0 | 704294 | 0.5870 |
| 0.6381 | 30.0 | 728580 | 0.5816 |
| 0.6306 | 31.0 | 752866 | 0.5813 |
| 0.6385 | 32.0 | 777152 | 0.5838 |
| 0.6338 | 33.0 | 801438 | 0.5808 |
| 0.6331 | 34.0 | 825724 | 0.5806 |
| 0.6235 | 35.0 | 850010 | 0.5825 |
| 0.6329 | 36.0 | 874296 | 0.5825 |
| 0.6338 | 37.0 | 898582 | 0.5810 |
| 0.6257 | 38.0 | 922868 | 0.5803 |
| 0.6268 | 39.0 | 947154 | 0.5810 |
| 0.6371 | 40.0 | 971440 | 0.5759 |
| 0.6272 | 41.0 | 995726 | 0.5775 |
| 0.6276 | 42.0 | 1020012 | 0.5771 |
| 0.635 | 43.0 | 1044298 | 0.5757 |
| 0.6314 | 44.0 | 1068584 | 0.5753 |
| 0.6279 | 45.0 | 1092870 | 0.5760 |
| 0.6186 | 46.0 | 1117156 | 0.5756 |
| 0.6214 | 47.0 | 1141442 | 0.5763 |
| 0.6257 | 48.0 | 1165728 | 0.5776 |
| 0.6272 | 49.0 | 1190014 | 0.5746 |
| 0.6291 | 50.0 | 1214300 | 0.5734 |
| 0.6311 | 51.0 | 1238586 | 0.5715 |
| 0.6279 | 52.0 | 1262872 | 0.5776 |
| 0.6372 | 53.0 | 1287158 | 0.5725 |
| 0.6155 | 54.0 | 1311444 | 0.5782 |
| 0.6241 | 55.0 | 1335730 | 0.5748 |
| 0.6187 | 56.0 | 1360016 | 0.5716 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.6.0.dev20241022+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
- Library
- transformers
- Type
- t5
- Created
- Dec 9, 2024
- Updated
- Dec 9, 2024