Downloads · 30 days
6
23% of all-time downloads
receipt-operations-model
DanSarm/receipt-operations-model
receipt-operations-model is a machine learning model from DanSarm. 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. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
All-time downloads
26
Public
Parameters
223M
4.7 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors892 MB · 100%
At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Jan 29, 2025
- Updated
- Mar 26, 2025
- SHA
- 7a8b2eb9
Base models
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. -->
receipt-operations-model
This model is a fine-tuned version of DanSarm/receipt-core-model on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0971
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: 4
- eval_batch_size: 4
- seed: 42
- 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
- num_epochs: 300
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.3532 | 1.0 | 29 | 0.2037 |
| 0.1308 | 2.0 | 58 | 0.1489 |
| 0.0937 | 3.0 | 87 | 0.1171 |
| 0.073 | 4.0 | 116 | 0.1048 |
| 0.0555 | 5.0 | 145 | 0.1018 |
| 0.0498 | 6.0 | 174 | 0.1001 |
| 0.0377 | 7.0 | 203 | 0.1025 |
| 0.0305 | 8.0 | 232 | 0.1047 |
| 0.0277 | 9.0 | 261 | 0.0971 |
| 0.0258 | 10.0 | 290 | 0.0977 |
| 0.0199 | 11.0 | 319 | 0.0978 |
| 0.0184 | 12.0 | 348 | 0.1008 |
| 0.0144 | 13.0 | 377 | 0.1051 |
| 0.0129 | 14.0 | 406 | 0.1076 |
| 0.0139 | 15.0 | 435 | 0.1072 |
| 0.0123 | 16.0 | 464 | 0.1100 |
| 0.0108 | 17.0 | 493 | 0.1086 |
| 0.0087 | 18.0 | 522 | 0.1124 |
| 0.0081 | 19.0 | 551 | 0.1212 |
| 0.0069 | 20.0 | 580 | 0.1219 |
| 0.0063 | 21.0 | 609 | 0.1131 |
| 0.004 | 22.0 | 638 | 0.1173 |
| 0.0053 | 23.0 | 667 | 0.1175 |
| 0.0058 | 24.0 | 696 | 0.1228 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Jan 29, 2025
- Updated
- Mar 26, 2025