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---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: pretrained-hist-l2_tenKQ_finetune-itemseg_v12-tssp-m0
results: []
---
<!-- 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. -->
# pretrained-hist-l2_tenKQ_finetune-itemseg_v12-tssp-m0
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3248
- Accuracy: 0.9294
- Macro F1: 0.8204
## 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: 16
- eval_batch_size: 16
- 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
- lr_scheduler_warmup_steps: 3365
- training_steps: 67312
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 |
|:-------------:|:--------:|:-----:|:---------------:|:--------:|:--------:|
| 18.3081 | 2.0010 | 201 | 92.0443 | 0.1413 | 0.0501 |
| 6.328 | 5.0009 | 402 | 133.2266 | 0.5761 | 0.1625 |
| 4.838 | 8.0009 | 603 | 145.9778 | 0.6359 | 0.1990 |
| 3.6763 | 11.0008 | 804 | 119.4216 | 0.6674 | 0.2212 |
| 2.7128 | 14.0008 | 1005 | 51.8430 | 0.7070 | 0.2573 |
| 2.3342 | 17.0007 | 1206 | 27.4778 | 0.7250 | 0.2894 |
| 1.8815 | 20.0007 | 1407 | 19.0125 | 0.7462 | 0.3373 |
| 1.65 | 23.0007 | 1608 | 13.0926 | 0.7608 | 0.3662 |
| 1.4902 | 26.0006 | 1809 | 8.4115 | 0.7567 | 0.4072 |
| 1.2953 | 29.0006 | 2010 | 7.8777 | 0.7823 | 0.4407 |
| 1.1867 | 32.0005 | 2211 | 6.7955 | 0.7812 | 0.4557 |
| 1.0704 | 35.0005 | 2412 | 5.3807 | 0.7841 | 0.4912 |
| 0.9792 | 38.0004 | 2613 | 4.6642 | 0.8160 | 0.5335 |
| 0.8649 | 41.0004 | 2814 | 4.1745 | 0.8178 | 0.5658 |
| 0.7768 | 44.0003 | 3015 | 3.8817 | 0.8240 | 0.5736 |
| 0.7169 | 47.0003 | 3216 | 4.2183 | 0.8330 | 0.5971 |
| 0.6459 | 50.0003 | 3417 | 3.4359 | 0.8295 | 0.6069 |
| 0.5664 | 53.0002 | 3618 | 3.3957 | 0.8538 | 0.6294 |
| 0.516 | 56.0002 | 3819 | 3.8816 | 0.8540 | 0.6424 |
| 0.4745 | 59.0001 | 4020 | 3.9219 | 0.8692 | 0.6628 |
| 0.4204 | 62.0001 | 4221 | 3.8606 | 0.8709 | 0.6657 |
| 0.3926 | 65.0000 | 4422 | 4.2133 | 0.8666 | 0.6703 |
| 0.3569 | 67.0010 | 4623 | 4.5565 | 0.8644 | 0.6744 |
| 0.3342 | 70.0010 | 4824 | 4.9640 | 0.8809 | 0.6919 |
| 0.303 | 73.0009 | 5025 | 5.1881 | 0.8813 | 0.7000 |
| 0.2858 | 76.0009 | 5226 | 5.0722 | 0.8878 | 0.7098 |
| 0.2741 | 79.0008 | 5427 | 6.1618 | 0.8920 | 0.7198 |
| 0.2592 | 82.0008 | 5628 | 6.5562 | 0.8897 | 0.7178 |
| 0.2432 | 85.0007 | 5829 | 7.2766 | 0.8939 | 0.7291 |
| 0.2265 | 88.0007 | 6030 | 8.0923 | 0.8949 | 0.7300 |
| 0.2201 | 91.0006 | 6231 | 7.3557 | 0.8984 | 0.7339 |
| 0.2093 | 94.0006 | 6432 | 7.3704 | 0.8954 | 0.7321 |
| 0.1983 | 97.0005 | 6633 | 8.7920 | 0.8962 | 0.7394 |
| 0.195 | 100.0005 | 6834 | 8.1665 | 0.8975 | 0.7421 |
| 0.1828 | 103.0005 | 7035 | 7.8452 | 0.9033 | 0.7492 |
| 0.18 | 106.0004 | 7236 | 7.6154 | 0.9012 | 0.7537 |
| 0.1723 | 109.0004 | 7437 | 6.4922 | 0.9060 | 0.7585 |
| 0.1694 | 112.0003 | 7638 | 7.5438 | 0.9040 | 0.7616 |
| 0.1672 | 115.0003 | 7839 | 6.9874 | 0.9053 | 0.7650 |
| 0.1552 | 118.0002 | 8040 | 7.1907 | 0.9063 | 0.7634 |
| 0.1588 | 121.0002 | 8241 | 7.0263 | 0.9086 | 0.7636 |
| 0.1509 | 124.0001 | 8442 | 6.8458 | 0.9070 | 0.7644 |
| 0.1514 | 127.0001 | 8643 | 5.4099 | 0.9089 | 0.7701 |
| 0.1457 | 130.0001 | 8844 | 5.8632 | 0.9107 | 0.7727 |
| 0.1425 | 133.0000 | 9045 | 5.6742 | 0.9111 | 0.7753 |
| 0.1415 | 135.0010 | 9246 | 5.7430 | 0.9117 | 0.7761 |
| 0.1436 | 138.0009 | 9447 | 5.0272 | 0.9103 | 0.7734 |
| 0.1434 | 141.0009 | 9648 | 4.4936 | 0.9096 | 0.7746 |
| 0.1377 | 144.0008 | 9849 | 5.2322 | 0.9078 | 0.7769 |
| 0.1383 | 147.0008 | 10050 | 4.7013 | 0.9149 | 0.7835 |
| 0.133 | 150.0008 | 10251 | 4.6257 | 0.9142 | 0.7836 |
| 0.1349 | 153.0007 | 10452 | 3.9570 | 0.9153 | 0.7830 |
| 0.1273 | 156.0007 | 10653 | 3.6838 | 0.9142 | 0.7806 |
| 0.1255 | 159.0006 | 10854 | 3.6121 | 0.9144 | 0.7836 |
| 0.1247 | 162.0006 | 11055 | 3.2919 | 0.9160 | 0.7879 |
| 0.129 | 165.0005 | 11256 | 3.1283 | 0.9132 | 0.7823 |
| 0.1215 | 168.0005 | 11457 | 3.2925 | 0.9152 | 0.7854 |
| 0.1216 | 171.0004 | 11658 | 3.1251 | 0.9168 | 0.7869 |
| 0.1205 | 174.0004 | 11859 | 3.1548 | 0.9182 | 0.7893 |
| 0.1231 | 177.0004 | 12060 | 2.7044 | 0.9122 | 0.7835 |
| 0.1308 | 180.0003 | 12261 | 2.7894 | 0.9158 | 0.7891 |
| 0.1254 | 183.0003 | 12462 | 2.6146 | 0.9158 | 0.7864 |
| 0.1194 | 186.0002 | 12663 | 2.9000 | 0.9179 | 0.7899 |
| 0.1171 | 189.0002 | 12864 | 2.7811 | 0.9157 | 0.7899 |
| 0.1159 | 192.0001 | 13065 | 2.6063 | 0.9180 | 0.7926 |
| 0.1164 | 195.0001 | 13266 | 2.7002 | 0.9180 | 0.7915 |
| 0.1148 | 198.0000 | 13467 | 2.5541 | 0.9192 | 0.7946 |
| 0.1172 | 200.0010 | 13668 | 2.3960 | 0.9173 | 0.7894 |
| 0.1252 | 203.0010 | 13869 | 2.2429 | 0.9164 | 0.7887 |
| 0.1122 | 206.0009 | 14070 | 2.1204 | 0.9187 | 0.7935 |
| 0.115 | 209.0009 | 14271 | 2.3396 | 0.9190 | 0.7961 |
| 0.108 | 212.0008 | 14472 | 2.0145 | 0.9198 | 0.7957 |
| 0.1081 | 215.0008 | 14673 | 2.1137 | 0.9202 | 0.7969 |
| 0.1093 | 218.0007 | 14874 | 2.0863 | 0.9205 | 0.7972 |
| 0.1073 | 221.0007 | 15075 | 1.8909 | 0.9196 | 0.7946 |
| 0.11 | 224.0007 | 15276 | 1.8784 | 0.9212 | 0.7977 |
| 0.1087 | 227.0006 | 15477 | 1.8960 | 0.9224 | 0.8016 |
| 0.1065 | 230.0006 | 15678 | 1.8995 | 0.9186 | 0.7946 |
| 0.1065 | 233.0005 | 15879 | 1.8899 | 0.9200 | 0.7968 |
| 0.1108 | 236.0005 | 16080 | 1.8815 | 0.9205 | 0.7982 |
| 0.1064 | 239.0004 | 16281 | 1.8124 | 0.9220 | 0.7989 |
| 0.1038 | 242.0004 | 16482 | 1.8478 | 0.9235 | 0.8016 |
| 0.1047 | 245.0003 | 16683 | 1.8597 | 0.9218 | 0.8015 |
| 0.1042 | 248.0003 | 16884 | 1.8254 | 0.9221 | 0.8011 |
| 0.1064 | 251.0003 | 17085 | 1.7683 | 0.9222 | 0.8005 |
| 0.1007 | 254.0002 | 17286 | 1.7810 | 0.9216 | 0.8044 |
| 0.1009 | 257.0002 | 17487 | 1.8142 | 0.9225 | 0.8025 |
| 0.1011 | 260.0001 | 17688 | 1.7981 | 0.9203 | 0.7992 |
| 0.0963 | 263.0001 | 17889 | 1.6290 | 0.9222 | 0.8056 |
| 0.1089 | 266.0000 | 18090 | 1.6993 | 0.9214 | 0.8007 |
| 0.1119 | 268.0010 | 18291 | 1.6256 | 0.9214 | 0.8022 |
| 0.1008 | 271.0010 | 18492 | 1.7093 | 0.9232 | 0.8026 |
| 0.0963 | 274.0009 | 18693 | 1.6050 | 0.9234 | 0.8048 |
| 0.0997 | 277.0009 | 18894 | 1.5403 | 0.9237 | 0.8080 |
| 0.0978 | 280.0008 | 19095 | 1.6604 | 0.9229 | 0.8034 |
| 0.0964 | 283.0008 | 19296 | 1.5679 | 0.9232 | 0.8071 |
| 0.0963 | 286.0007 | 19497 | 1.5459 | 0.9230 | 0.8048 |
| 0.0973 | 289.0007 | 19698 | 1.4886 | 0.9196 | 0.8025 |
| 0.0996 | 292.0006 | 19899 | 1.4917 | 0.9208 | 0.8024 |
| 0.0963 | 295.0006 | 20100 | 1.3997 | 0.9225 | 0.8051 |
| 0.095 | 298.0005 | 20301 | 1.4833 | 0.9228 | 0.8050 |
| 0.0955 | 301.0005 | 20502 | 1.5128 | 0.9217 | 0.8033 |
| 0.0969 | 304.0005 | 20703 | 1.4938 | 0.9208 | 0.8025 |
| 0.1025 | 307.0004 | 20904 | 1.5228 | 0.9236 | 0.8031 |
| 0.096 | 310.0004 | 21105 | 1.5700 | 0.9241 | 0.8084 |
| 0.0981 | 313.0003 | 21306 | 1.4501 | 0.9202 | 0.8003 |
| 0.0968 | 316.0003 | 21507 | 1.5587 | 0.9238 | 0.8046 |
| 0.0958 | 319.0002 | 21708 | 1.4369 | 0.9254 | 0.8081 |
| 0.091 | 322.0002 | 21909 | 1.4935 | 0.9251 | 0.8074 |
| 0.0945 | 325.0001 | 22110 | 1.4459 | 0.9269 | 0.8120 |
| 0.0923 | 328.0001 | 22311 | 1.3652 | 0.9259 | 0.8109 |
| 0.0916 | 331.0001 | 22512 | 1.5116 | 0.9260 | 0.8099 |
| 0.091 | 334.0000 | 22713 | 1.4167 | 0.9245 | 0.8084 |
| 0.0924 | 336.0010 | 22914 | 1.4038 | 0.9258 | 0.8095 |
| 0.0917 | 339.0009 | 23115 | 1.4282 | 0.9258 | 0.8103 |
| 0.0892 | 342.0009 | 23316 | 1.4295 | 0.9267 | 0.8108 |
| 0.0898 | 345.0008 | 23517 | 1.4366 | 0.9257 | 0.8137 |
| 0.0916 | 348.0008 | 23718 | 1.4560 | 0.9234 | 0.8075 |
| 0.088 | 351.0008 | 23919 | 1.3876 | 0.9258 | 0.8118 |
| 0.0896 | 354.0007 | 24120 | 1.5172 | 0.9227 | 0.8065 |
| 0.088 | 357.0007 | 24321 | 1.5016 | 0.9261 | 0.8097 |
| 0.0874 | 360.0006 | 24522 | 1.4182 | 0.9254 | 0.8089 |
| 0.0918 | 363.0006 | 24723 | 1.4840 | 0.9241 | 0.8045 |
| 0.09 | 366.0005 | 24924 | 1.5154 | 0.9233 | 0.8081 |
| 0.0888 | 369.0005 | 25125 | 1.3604 | 0.9277 | 0.8143 |
| 0.0866 | 372.0004 | 25326 | 1.4135 | 0.9240 | 0.8081 |
| 0.089 | 375.0004 | 25527 | 1.4785 | 0.9260 | 0.8117 |
| 0.0928 | 378.0004 | 25728 | 1.3908 | 0.9256 | 0.8094 |
| 0.0927 | 381.0003 | 25929 | 1.4106 | 0.9246 | 0.8058 |
| 0.0877 | 384.0003 | 26130 | 1.3791 | 0.9263 | 0.8111 |
| 0.0859 | 387.0002 | 26331 | 1.4158 | 0.9256 | 0.8112 |
| 0.0878 | 390.0002 | 26532 | 1.3359 | 0.9256 | 0.8111 |
| 0.085 | 393.0001 | 26733 | 1.3835 | 0.9249 | 0.8096 |
| 0.0863 | 396.0001 | 26934 | 1.3753 | 0.9255 | 0.8109 |
| 0.0854 | 399.0000 | 27135 | 1.3575 | 0.9266 | 0.8108 |
| 0.0856 | 401.0010 | 27336 | 1.3802 | 0.9270 | 0.8122 |
| 0.0856 | 404.0010 | 27537 | 1.3584 | 0.9278 | 0.8138 |
| 0.0868 | 407.0009 | 27738 | 1.4511 | 0.9240 | 0.8079 |
| 0.0866 | 410.0009 | 27939 | 1.3532 | 0.9270 | 0.8125 |
| 0.0843 | 413.0008 | 28140 | 1.3818 | 0.9264 | 0.8134 |
| 0.086 | 416.0008 | 28341 | 1.3797 | 0.9262 | 0.8131 |
| 0.0849 | 419.0007 | 28542 | 1.3713 | 0.9267 | 0.8149 |
| 0.0831 | 422.0007 | 28743 | 1.4248 | 0.9260 | 0.8123 |
| 0.0843 | 425.0007 | 28944 | 1.3671 | 0.9272 | 0.8133 |
| 0.0838 | 428.0006 | 29145 | 1.5038 | 0.9260 | 0.8124 |
| 0.0839 | 431.0006 | 29346 | 1.4157 | 0.9272 | 0.8136 |
| 0.0827 | 434.0005 | 29547 | 1.3950 | 0.9269 | 0.8137 |
| 0.0832 | 437.0005 | 29748 | 1.3595 | 0.9267 | 0.8128 |
| 0.0867 | 440.0004 | 29949 | 1.2980 | 0.9243 | 0.8134 |
| 0.0846 | 443.0004 | 30150 | 1.4668 | 0.9279 | 0.8149 |
| 0.0853 | 446.0003 | 30351 | 1.3490 | 0.9259 | 0.8133 |
| 0.0849 | 449.0003 | 30552 | 1.4092 | 0.9275 | 0.8148 |
| 0.0856 | 452.0003 | 30753 | 1.3654 | 0.9246 | 0.8077 |
| 0.0838 | 455.0002 | 30954 | 1.4238 | 0.9269 | 0.8115 |
| 0.0809 | 458.0002 | 31155 | 1.3319 | 0.9273 | 0.8117 |
| 0.0826 | 461.0001 | 31356 | 1.4123 | 0.9276 | 0.8129 |
| 0.0815 | 464.0001 | 31557 | 1.3352 | 0.9275 | 0.8136 |
| 0.0804 | 467.0000 | 31758 | 1.3803 | 0.9280 | 0.8159 |
| 0.0797 | 469.0010 | 31959 | 1.3948 | 0.9272 | 0.8173 |
| 0.0806 | 472.0010 | 32160 | 1.3945 | 0.9261 | 0.8104 |
| 0.0804 | 475.0009 | 32361 | 1.3707 | 0.9284 | 0.8156 |
| 0.0808 | 478.0009 | 32562 | 1.4406 | 0.9268 | 0.8152 |
| 0.0792 | 481.0008 | 32763 | 1.4056 | 0.9267 | 0.8144 |
| 0.0788 | 484.0008 | 32964 | 1.4086 | 0.9269 | 0.8145 |
| 0.0805 | 487.0007 | 33165 | 1.3563 | 0.9276 | 0.8168 |
| 0.0804 | 490.0007 | 33366 | 1.3429 | 0.9284 | 0.8149 |
| 0.0798 | 493.0006 | 33567 | 1.4408 | 0.9270 | 0.8143 |
| 0.0791 | 496.0006 | 33768 | 1.4209 | 0.9274 | 0.8152 |
| 0.0823 | 499.0005 | 33969 | 1.4354 | 0.9271 | 0.8144 |
| 0.0811 | 502.0005 | 34170 | 1.3956 | 0.9265 | 0.8146 |
| 0.0978 | 505.0005 | 34371 | 1.4652 | 0.9256 | 0.8102 |
| 0.0894 | 508.0004 | 34572 | 1.3084 | 0.9237 | 0.8135 |
| 0.0817 | 511.0004 | 34773 | 1.3392 | 0.9272 | 0.8169 |
| 0.0793 | 514.0003 | 34974 | 1.3396 | 0.9294 | 0.8198 |
| 0.0781 | 517.0003 | 35175 | 1.2850 | 0.9289 | 0.8204 |
| 0.0787 | 520.0002 | 35376 | 1.3228 | 0.9294 | 0.8204 |
| 0.0778 | 523.0002 | 35577 | 1.3750 | 0.9289 | 0.8172 |
| 0.0772 | 526.0001 | 35778 | 1.4147 | 0.9274 | 0.8143 |
| 0.0777 | 529.0001 | 35979 | 1.3052 | 0.9278 | 0.8170 |
| 0.0783 | 532.0001 | 36180 | 1.2464 | 0.9286 | 0.8198 |
| 0.077 | 535.0000 | 36381 | 1.3571 | 0.9283 | 0.8184 |
| 0.0778 | 537.0010 | 36582 | 1.3503 | 0.9290 | 0.8184 |
| 0.0787 | 540.0009 | 36783 | 1.3391 | 0.9286 | 0.8184 |
| 0.077 | 543.0009 | 36984 | 1.4027 | 0.9292 | 0.8170 |
| 0.0779 | 546.0008 | 37185 | 1.3167 | 0.9281 | 0.8165 |
| 0.0781 | 549.0008 | 37386 | 1.3828 | 0.9284 | 0.8147 |
| 0.0781 | 552.0008 | 37587 | 1.3284 | 0.9287 | 0.8196 |
| 0.0765 | 555.0007 | 37788 | 1.4137 | 0.9286 | 0.8186 |
| 0.0778 | 558.0007 | 37989 | 1.4190 | 0.9286 | 0.8174 |
| 0.0747 | 561.0006 | 38190 | 1.3886 | 0.9289 | 0.8159 |
| 0.0768 | 564.0006 | 38391 | 1.3433 | 0.9291 | 0.8178 |
| 0.0765 | 567.0005 | 38592 | 1.4049 | 0.9289 | 0.8169 |
| 0.0781 | 570.0005 | 38793 | 1.4670 | 0.9276 | 0.8141 |
| 0.0776 | 573.0004 | 38994 | 1.5075 | 0.9280 | 0.8166 |
| 0.0753 | 576.0004 | 39195 | 1.3683 | 0.9280 | 0.8164 |
| 0.0756 | 579.0004 | 39396 | 1.3317 | 0.9281 | 0.8186 |
### Framework versions
- Transformers 4.46.0
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.20.1
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