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bankstatementmodelver1
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 5.9506
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: 0.01
- train_batch_size: 16
- eval_batch_size: 11
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 250 | 5.9506 |
| 5.9757 | 2.0 | 500 | 5.9506 |
| 5.9757 | 3.0 | 750 | 5.9506 |
| 5.9729 | 4.0 | 1000 | 5.9506 |
| 5.9729 | 5.0 | 1250 | 5.9506 |
| 5.9635 | 6.0 | 1500 | 5.9506 |
| 5.9635 | 7.0 | 1750 | 5.9506 |
| 5.9611 | 8.0 | 2000 | 5.9506 |
| 5.9611 | 9.0 | 2250 | 5.9506 |
| 5.9607 | 10.0 | 2500 | 5.9506 |
| 5.9607 | 11.0 | 2750 | 5.9506 |
| 5.96 | 12.0 | 3000 | 5.9506 |
| 5.96 | 13.0 | 3250 | 5.9506 |
| 5.9608 | 14.0 | 3500 | 5.9506 |
| 5.9608 | 15.0 | 3750 | 5.9506 |
| 5.9588 | 16.0 | 4000 | 5.9506 |
| 5.9588 | 17.0 | 4250 | 5.9506 |
| 5.9584 | 18.0 | 4500 | 5.9506 |
| 5.9584 | 19.0 | 4750 | 5.9506 |
| 5.9581 | 20.0 | 5000 | 5.9506 |
| 5.9581 | 21.0 | 5250 | 5.9506 |
| 5.9558 | 22.0 | 5500 | 5.9506 |
| 5.9558 | 23.0 | 5750 | 5.9506 |
| 5.9558 | 24.0 | 6000 | 5.9506 |
| 5.9558 | 25.0 | 6250 | 5.9506 |
| 5.9557 | 26.0 | 6500 | 5.9506 |
| 5.9557 | 27.0 | 6750 | 5.9506 |
| 5.955 | 28.0 | 7000 | 5.9506 |
| 5.955 | 29.0 | 7250 | 5.9506 |
| 5.9537 | 30.0 | 7500 | 5.9506 |
| 5.9537 | 31.0 | 7750 | 5.9506 |
| 5.9535 | 32.0 | 8000 | 5.9506 |
| 5.9535 | 33.0 | 8250 | 5.9506 |
| 5.9528 | 34.0 | 8500 | 5.9506 |
| 5.9528 | 35.0 | 8750 | 5.9506 |
| 5.9529 | 36.0 | 9000 | 5.9506 |
| 5.9529 | 37.0 | 9250 | 5.9506 |
| 5.9525 | 38.0 | 9500 | 5.9506 |
| 5.9525 | 39.0 | 9750 | 5.9506 |
| 5.9516 | 40.0 | 10000 | 5.9506 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
