
<!-- 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. -->

# vit-base-lcdoctypev1_session2

This model is a fine-tuned version of [nsugianto/vit-base-lcdoctypev1](https://huggingface.co/nsugianto/vit-base-lcdoctypev1) on the doctype_v1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1231
- Accuracy: 0.9752

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.08  | 5    | 0.3652          | 0.9008   |
| 0.2494        | 0.17  | 10   | 0.4354          | 0.8926   |
| 0.2494        | 0.25  | 15   | 0.6027          | 0.8264   |
| 0.4714        | 0.33  | 20   | 0.6016          | 0.8182   |
| 0.4714        | 0.42  | 25   | 0.6495          | 0.8017   |
| 0.6257        | 0.5   | 30   | 0.6561          | 0.7769   |
| 0.6257        | 0.58  | 35   | 0.4359          | 0.8264   |
| 0.3534        | 0.67  | 40   | 0.4082          | 0.8760   |
| 0.3534        | 0.75  | 45   | 0.3042          | 0.9174   |
| 0.2059        | 0.83  | 50   | 0.3919          | 0.8843   |
| 0.2059        | 0.92  | 55   | 0.9259          | 0.7521   |
| 0.3693        | 1.0   | 60   | 0.5527          | 0.8430   |
| 0.3693        | 1.08  | 65   | 0.3412          | 0.8595   |
| 0.3436        | 1.17  | 70   | 0.3949          | 0.8595   |
| 0.3436        | 1.25  | 75   | 0.4402          | 0.8760   |
| 0.361         | 1.33  | 80   | 0.8712          | 0.7355   |
| 0.361         | 1.42  | 85   | 0.4137          | 0.8430   |
| 0.4531        | 1.5   | 90   | 0.2484          | 0.9256   |
| 0.4531        | 1.58  | 95   | 0.3072          | 0.9008   |
| 0.223         | 1.67  | 100  | 0.3936          | 0.9008   |
| 0.223         | 1.75  | 105  | 0.4798          | 0.8595   |
| 0.3396        | 1.83  | 110  | 0.3731          | 0.8760   |
| 0.3396        | 1.92  | 115  | 0.3138          | 0.9174   |
| 0.1516        | 2.0   | 120  | 0.3140          | 0.9008   |
| 0.1516        | 2.08  | 125  | 0.3938          | 0.8926   |
| 0.1709        | 2.17  | 130  | 0.3311          | 0.9174   |
| 0.1709        | 2.25  | 135  | 0.3652          | 0.9091   |
| 0.1193        | 2.33  | 140  | 0.4033          | 0.9008   |
| 0.1193        | 2.42  | 145  | 0.3220          | 0.8926   |
| 0.2134        | 2.5   | 150  | 0.4836          | 0.8595   |
| 0.2134        | 2.58  | 155  | 0.2969          | 0.9091   |
| 0.1314        | 2.67  | 160  | 0.3032          | 0.9174   |
| 0.1314        | 2.75  | 165  | 0.3466          | 0.8843   |
| 0.2197        | 2.83  | 170  | 0.2749          | 0.8843   |
| 0.2197        | 2.92  | 175  | 0.2071          | 0.9256   |
| 0.1748        | 3.0   | 180  | 0.2477          | 0.9256   |
| 0.1748        | 3.08  | 185  | 0.2279          | 0.9174   |
| 0.0949        | 3.17  | 190  | 0.2859          | 0.9091   |
| 0.0949        | 3.25  | 195  | 0.2731          | 0.9008   |
| 0.1901        | 3.33  | 200  | 0.2329          | 0.9339   |
| 0.1901        | 3.42  | 205  | 0.4313          | 0.9008   |
| 0.1897        | 3.5   | 210  | 0.3919          | 0.9008   |
| 0.1897        | 3.58  | 215  | 0.2083          | 0.9504   |
| 0.1213        | 3.67  | 220  | 0.2194          | 0.9421   |
| 0.1213        | 3.75  | 225  | 0.2504          | 0.9421   |
| 0.1225        | 3.83  | 230  | 0.2727          | 0.9339   |
| 0.1225        | 3.92  | 235  | 0.5615          | 0.8595   |
| 0.148         | 4.0   | 240  | 0.3485          | 0.9091   |
| 0.148         | 4.08  | 245  | 0.2324          | 0.9008   |
| 0.1498        | 4.17  | 250  | 0.2689          | 0.9256   |
| 0.1498        | 4.25  | 255  | 0.1947          | 0.9504   |
| 0.0504        | 4.33  | 260  | 0.2275          | 0.9339   |
| 0.0504        | 4.42  | 265  | 0.2790          | 0.9339   |
| 0.0465        | 4.5   | 270  | 0.2727          | 0.9256   |
| 0.0465        | 4.58  | 275  | 0.2949          | 0.9256   |
| 0.0744        | 4.67  | 280  | 0.2705          | 0.9421   |
| 0.0744        | 4.75  | 285  | 0.2787          | 0.9339   |
| 0.1504        | 4.83  | 290  | 0.2361          | 0.9421   |
| 0.1504        | 4.92  | 295  | 0.2886          | 0.9256   |
| 0.1192        | 5.0   | 300  | 0.2602          | 0.9256   |
| 0.1192        | 5.08  | 305  | 0.2183          | 0.9256   |
| 0.0749        | 5.17  | 310  | 0.2774          | 0.9174   |
| 0.0749        | 5.25  | 315  | 0.2491          | 0.9091   |
| 0.0719        | 5.33  | 320  | 0.1902          | 0.9504   |
| 0.0719        | 5.42  | 325  | 0.1915          | 0.9504   |
| 0.061         | 5.5   | 330  | 0.1713          | 0.9587   |
| 0.061         | 5.58  | 335  | 0.2117          | 0.9504   |
| 0.0381        | 5.67  | 340  | 0.2145          | 0.9587   |
| 0.0381        | 5.75  | 345  | 0.2108          | 0.9504   |
| 0.0494        | 5.83  | 350  | 0.2006          | 0.9504   |
| 0.0494        | 5.92  | 355  | 0.1935          | 0.9504   |
| 0.0341        | 6.0   | 360  | 0.1891          | 0.9669   |
| 0.0341        | 6.08  | 365  | 0.1675          | 0.9669   |
| 0.0186        | 6.17  | 370  | 0.1582          | 0.9669   |
| 0.0186        | 6.25  | 375  | 0.1470          | 0.9669   |
| 0.0444        | 6.33  | 380  | 0.1401          | 0.9752   |
| 0.0444        | 6.42  | 385  | 0.1611          | 0.9669   |
| 0.031         | 6.5   | 390  | 0.1923          | 0.9669   |
| 0.031         | 6.58  | 395  | 0.2467          | 0.9339   |
| 0.0415        | 6.67  | 400  | 0.1997          | 0.9587   |
| 0.0415        | 6.75  | 405  | 0.1741          | 0.9669   |
| 0.0396        | 6.83  | 410  | 0.1882          | 0.9669   |
| 0.0396        | 6.92  | 415  | 0.2266          | 0.9587   |
| 0.1419        | 7.0   | 420  | 0.2240          | 0.9587   |
| 0.1419        | 7.08  | 425  | 0.1832          | 0.9669   |
| 0.0401        | 7.17  | 430  | 0.1767          | 0.9587   |
| 0.0401        | 7.25  | 435  | 0.1653          | 0.9587   |
| 0.0435        | 7.33  | 440  | 0.1873          | 0.9421   |
| 0.0435        | 7.42  | 445  | 0.2051          | 0.9504   |
| 0.0368        | 7.5   | 450  | 0.2075          | 0.9504   |
| 0.0368        | 7.58  | 455  | 0.1932          | 0.9504   |
| 0.0144        | 7.67  | 460  | 0.1878          | 0.9504   |
| 0.0144        | 7.75  | 465  | 0.1855          | 0.9504   |
| 0.0245        | 7.83  | 470  | 0.1826          | 0.9587   |
| 0.0245        | 7.92  | 475  | 0.1652          | 0.9669   |
| 0.049         | 8.0   | 480  | 0.1540          | 0.9669   |
| 0.049         | 8.08  | 485  | 0.1566          | 0.9587   |
| 0.0205        | 8.17  | 490  | 0.1390          | 0.9587   |
| 0.0205        | 8.25  | 495  | 0.1231          | 0.9752   |
| 0.0582        | 8.33  | 500  | 0.1489          | 0.9669   |
| 0.0582        | 8.42  | 505  | 0.1636          | 0.9669   |
| 0.0233        | 8.5   | 510  | 0.1738          | 0.9587   |
| 0.0233        | 8.58  | 515  | 0.1830          | 0.9587   |
| 0.026         | 8.67  | 520  | 0.1868          | 0.9587   |
| 0.026         | 8.75  | 525  | 0.1848          | 0.9587   |
| 0.0193        | 8.83  | 530  | 0.1805          | 0.9669   |
| 0.0193        | 8.92  | 535  | 0.1774          | 0.9669   |
| 0.0174        | 9.0   | 540  | 0.1709          | 0.9669   |
| 0.0174        | 9.08  | 545  | 0.1626          | 0.9587   |
| 0.036         | 9.17  | 550  | 0.1482          | 0.9669   |
| 0.036         | 9.25  | 555  | 0.1522          | 0.9669   |
| 0.0248        | 9.33  | 560  | 0.1524          | 0.9669   |
| 0.0248        | 9.42  | 565  | 0.1530          | 0.9669   |
| 0.0097        | 9.5   | 570  | 0.1537          | 0.9669   |
| 0.0097        | 9.58  | 575  | 0.1546          | 0.9669   |
| 0.0154        | 9.67  | 580  | 0.1550          | 0.9669   |
| 0.0154        | 9.75  | 585  | 0.1554          | 0.9669   |
| 0.0208        | 9.83  | 590  | 0.1549          | 0.9669   |
| 0.0208        | 9.92  | 595  | 0.1541          | 0.9669   |
| 0.0167        | 10.0  | 600  | 0.1542          | 0.9669   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2

creditnote invoice po rfq