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receipt-operations-model

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Fine-tuned Operations Receipt Model

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  1. README.md +22 -61
  2. model.safetensors +1 -1
  3. training_args.bin +2 -2
README.md CHANGED
@@ -16,7 +16,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [DanSarm/receipt-core-model](https://huggingface.co/DanSarm/receipt-core-model) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1278
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  ## Model description
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@@ -41,71 +41,32 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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- - num_epochs: 1000
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- - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 0.4517 | 1.0 | 19 | 0.2472 |
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- | 0.1736 | 2.0 | 38 | 0.1857 |
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- | 0.1242 | 3.0 | 57 | 0.1488 |
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- | 0.0957 | 4.0 | 76 | 0.1314 |
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- | 0.0691 | 5.0 | 95 | 0.1292 |
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- | 0.0546 | 6.0 | 114 | 0.1221 |
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- | 0.0456 | 7.0 | 133 | 0.1136 |
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- | 0.0422 | 8.0 | 152 | 0.1116 |
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- | 0.0321 | 9.0 | 171 | 0.1234 |
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- | 0.0266 | 10.0 | 190 | 0.1123 |
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- | 0.0228 | 11.0 | 209 | 0.1139 |
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- | 0.0213 | 12.0 | 228 | 0.1122 |
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- | 0.0201 | 13.0 | 247 | 0.1166 |
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- | 0.0188 | 14.0 | 266 | 0.1238 |
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- | 0.0146 | 15.0 | 285 | 0.1256 |
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- | 0.0134 | 16.0 | 304 | 0.1186 |
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- | 0.0124 | 17.0 | 323 | 0.1193 |
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- | 0.0108 | 18.0 | 342 | 0.1150 |
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- | 0.0084 | 19.0 | 361 | 0.1171 |
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- | 0.0077 | 20.0 | 380 | 0.1216 |
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- | 0.0082 | 21.0 | 399 | 0.1225 |
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- | 0.0073 | 22.0 | 418 | 0.1210 |
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- | 0.0066 | 23.0 | 437 | 0.1199 |
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- | 0.0083 | 24.0 | 456 | 0.1170 |
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- | 0.0087 | 25.0 | 475 | 0.1172 |
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- | 0.0053 | 26.0 | 494 | 0.1160 |
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- | 0.0061 | 27.0 | 513 | 0.1178 |
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- | 0.0045 | 28.0 | 532 | 0.1169 |
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- | 0.0048 | 29.0 | 551 | 0.1192 |
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- | 0.0034 | 30.0 | 570 | 0.1219 |
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- | 0.0032 | 31.0 | 589 | 0.1194 |
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- | 0.0038 | 32.0 | 608 | 0.1230 |
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- | 0.0036 | 33.0 | 627 | 0.1241 |
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- | 0.0036 | 34.0 | 646 | 0.1235 |
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- | 0.0039 | 35.0 | 665 | 0.1178 |
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- | 0.0025 | 36.0 | 684 | 0.1174 |
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- | 0.004 | 37.0 | 703 | 0.1146 |
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- | 0.003 | 38.0 | 722 | 0.1148 |
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- | 0.002 | 39.0 | 741 | 0.1186 |
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- | 0.0026 | 40.0 | 760 | 0.1137 |
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- | 0.0019 | 41.0 | 779 | 0.1134 |
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- | 0.0018 | 42.0 | 798 | 0.1135 |
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- | 0.0014 | 43.0 | 817 | 0.1139 |
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- | 0.0019 | 44.0 | 836 | 0.1189 |
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- | 0.0012 | 45.0 | 855 | 0.1153 |
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- | 0.0017 | 46.0 | 874 | 0.1155 |
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- | 0.0019 | 47.0 | 893 | 0.1181 |
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- | 0.0013 | 48.0 | 912 | 0.1189 |
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- | 0.0012 | 49.0 | 931 | 0.1231 |
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- | 0.0011 | 50.0 | 950 | 0.1211 |
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- | 0.0021 | 51.0 | 969 | 0.1217 |
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- | 0.002 | 52.0 | 988 | 0.1235 |
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- | 0.0022 | 53.0 | 1007 | 0.1193 |
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- | 0.0022 | 54.0 | 1026 | 0.1185 |
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- | 0.002 | 55.0 | 1045 | 0.1230 |
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- | 0.0014 | 56.0 | 1064 | 0.1246 |
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- | 0.0012 | 57.0 | 1083 | 0.1249 |
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- | 0.0014 | 58.0 | 1102 | 0.1278 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [DanSarm/receipt-core-model](https://huggingface.co/DanSarm/receipt-core-model) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0950
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  ## Model description
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  - seed: 42
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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+ - num_epochs: 20
 
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 0.3537 | 1.0 | 29 | 0.2147 |
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+ | 0.1355 | 2.0 | 58 | 0.1529 |
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+ | 0.0971 | 3.0 | 87 | 0.1183 |
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+ | 0.0765 | 4.0 | 116 | 0.1090 |
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+ | 0.0589 | 5.0 | 145 | 0.1075 |
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+ | 0.0538 | 6.0 | 174 | 0.1000 |
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+ | 0.0424 | 7.0 | 203 | 0.1012 |
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+ | 0.0363 | 8.0 | 232 | 0.0978 |
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+ | 0.0329 | 9.0 | 261 | 0.0995 |
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+ | 0.0289 | 10.0 | 290 | 0.0950 |
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+ | 0.0259 | 11.0 | 319 | 0.0972 |
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+ | 0.0246 | 12.0 | 348 | 0.0980 |
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+ | 0.0204 | 13.0 | 377 | 0.0960 |
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+ | 0.0195 | 14.0 | 406 | 0.0957 |
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+ | 0.0185 | 15.0 | 435 | 0.0955 |
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+ | 0.0193 | 16.0 | 464 | 0.0963 |
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+ | 0.0157 | 17.0 | 493 | 0.0959 |
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+ | 0.0149 | 18.0 | 522 | 0.0967 |
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+ | 0.0145 | 19.0 | 551 | 0.0973 |
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+ | 0.0138 | 20.0 | 580 | 0.0967 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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