--- library_name: transformers license: apache-2.0 base_model: DanSarm/receipt-core-model tags: - generated_from_trainer model-index: - name: receipt-core-model results: [] --- # receipt-core-model This model is a fine-tuned version of [DanSarm/receipt-core-model](https://huggingface.co/DanSarm/receipt-core-model) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.2194 ## 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: 1000 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 0.1872 | 1.0 | 36 | 0.8766 | | 0.1235 | 2.0 | 72 | 0.9059 | | 0.0904 | 3.0 | 108 | 0.9360 | | 0.0762 | 4.0 | 144 | 0.8768 | | 0.0652 | 5.0 | 180 | 0.9361 | | 0.054 | 6.0 | 216 | 0.9305 | | 0.047 | 7.0 | 252 | 0.9453 | | 0.0427 | 8.0 | 288 | 1.0083 | | 0.0375 | 9.0 | 324 | 1.0142 | | 0.0317 | 10.0 | 360 | 1.0458 | | 0.0303 | 11.0 | 396 | 1.0515 | | 0.0283 | 12.0 | 432 | 1.0791 | | 0.0259 | 13.0 | 468 | 1.0594 | | 0.0236 | 14.0 | 504 | 1.1078 | | 0.0213 | 15.0 | 540 | 1.0250 | | 0.0194 | 16.0 | 576 | 1.0492 | | 0.0158 | 17.0 | 612 | 1.0782 | | 0.016 | 18.0 | 648 | 1.1181 | | 0.0135 | 19.0 | 684 | 1.1222 | | 0.0138 | 20.0 | 720 | 1.1314 | | 0.013 | 21.0 | 756 | 1.1197 | | 0.0106 | 22.0 | 792 | 1.1216 | | 0.0106 | 23.0 | 828 | 1.1382 | | 0.0105 | 24.0 | 864 | 1.1542 | | 0.0084 | 25.0 | 900 | 1.1758 | | 0.0078 | 26.0 | 936 | 1.1630 | | 0.0071 | 27.0 | 972 | 1.1524 | | 0.007 | 28.0 | 1008 | 1.1615 | | 0.0049 | 29.0 | 1044 | 1.1673 | | 0.0062 | 30.0 | 1080 | 1.1623 | | 0.0057 | 31.0 | 1116 | 1.1709 | | 0.0046 | 32.0 | 1152 | 1.1976 | | 0.0043 | 33.0 | 1188 | 1.2217 | | 0.0035 | 34.0 | 1224 | 1.1863 | | 0.0051 | 35.0 | 1260 | 1.2208 | | 0.006 | 36.0 | 1296 | 1.1681 | | 0.0044 | 37.0 | 1332 | 1.1783 | | 0.0053 | 38.0 | 1368 | 1.1821 | | 0.0049 | 39.0 | 1404 | 1.1724 | | 0.0042 | 40.0 | 1440 | 1.1936 | | 0.0031 | 41.0 | 1476 | 1.2066 | | 0.0031 | 42.0 | 1512 | 1.2156 | | 0.0039 | 43.0 | 1548 | 1.2054 | | 0.0026 | 44.0 | 1584 | 1.2000 | | 0.0028 | 45.0 | 1620 | 1.2259 | | 0.0021 | 46.0 | 1656 | 1.2244 | | 0.0026 | 47.0 | 1692 | 1.2218 | | 0.0037 | 48.0 | 1728 | 1.2165 | | 0.003 | 49.0 | 1764 | 1.2012 | | 0.0021 | 50.0 | 1800 | 1.1950 | | 0.0026 | 51.0 | 1836 | 1.2444 | | 0.0024 | 52.0 | 1872 | 1.2066 | | 0.0023 | 53.0 | 1908 | 1.2075 | | 0.002 | 54.0 | 1944 | 1.2476 | | 0.0016 | 55.0 | 1980 | 1.2365 | | 0.0016 | 56.0 | 2016 | 1.2422 | | 0.0014 | 57.0 | 2052 | 1.2420 | | 0.0013 | 58.0 | 2088 | 1.2246 | | 0.002 | 59.0 | 2124 | 1.2482 | | 0.0014 | 60.0 | 2160 | 1.2752 | | 0.0014 | 61.0 | 2196 | 1.2494 | | 0.0013 | 62.0 | 2232 | 1.2648 | | 0.0018 | 63.0 | 2268 | 1.2743 | | 0.0027 | 64.0 | 2304 | 1.2162 | | 0.0019 | 65.0 | 2340 | 1.2315 | | 0.0016 | 66.0 | 2376 | 1.2573 | | 0.0012 | 67.0 | 2412 | 1.2511 | | 0.0018 | 68.0 | 2448 | 1.2632 | | 0.0022 | 69.0 | 2484 | 1.2582 | | 0.0015 | 70.0 | 2520 | 1.2676 | | 0.0011 | 71.0 | 2556 | 1.2798 | | 0.002 | 72.0 | 2592 | 1.2352 | | 0.0012 | 73.0 | 2628 | 1.2430 | | 0.0012 | 74.0 | 2664 | 1.2731 | | 0.001 | 75.0 | 2700 | 1.2773 | | 0.0009 | 76.0 | 2736 | 1.2506 | | 0.001 | 77.0 | 2772 | 1.2479 | | 0.0008 | 78.0 | 2808 | 1.2521 | | 0.0008 | 79.0 | 2844 | 1.2630 | | 0.0005 | 80.0 | 2880 | 1.2725 | | 0.0009 | 81.0 | 2916 | 1.2539 | | 0.0005 | 82.0 | 2952 | 1.2643 | | 0.0007 | 83.0 | 2988 | 1.2722 | | 0.001 | 84.0 | 3024 | 1.2690 | | 0.0007 | 85.0 | 3060 | 1.2914 | | 0.0006 | 86.0 | 3096 | 1.2911 | | 0.0007 | 87.0 | 3132 | 1.2977 | | 0.0007 | 88.0 | 3168 | 1.3432 | | 0.0008 | 89.0 | 3204 | 1.3392 | | 0.001 | 90.0 | 3240 | 1.2964 | | 0.0023 | 91.0 | 3276 | 1.2660 | | 0.0019 | 92.0 | 3312 | 1.2739 | | 0.0017 | 93.0 | 3348 | 1.2968 | | 0.0017 | 94.0 | 3384 | 1.3048 | | 0.0014 | 95.0 | 3420 | 1.3139 | | 0.0017 | 96.0 | 3456 | 1.3031 | | 0.0012 | 97.0 | 3492 | 1.2952 | | 0.0014 | 98.0 | 3528 | 1.3281 | | 0.0021 | 99.0 | 3564 | 1.3087 | | 0.0024 | 100.0 | 3600 | 1.2122 | | 0.0028 | 101.0 | 3636 | 1.2194 | ### Framework versions - Transformers 4.49.0 - Pytorch 2.6.0+cu124 - Datasets 3.3.1 - Tokenizers 0.21.0