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detr_finetuned_cppe5

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conditional_detr
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README.md CHANGED
@@ -16,28 +16,28 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/conditional-detr-resnet-50](https://huggingface.co/microsoft/conditional-detr-resnet-50) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.2957
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- - Map: 0.1854
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- - Map 50: 0.3967
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- - Map 75: 0.1509
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- - Map Small: 0.075
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- - Map Medium: 0.1538
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- - Map Large: 0.2634
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- - Mar 1: 0.2171
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- - Mar 10: 0.382
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- - Mar 100: 0.4106
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- - Mar Small: 0.1542
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- - Mar Medium: 0.3591
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- - Mar Large: 0.5679
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- - Map Coverall: 0.4319
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- - Mar 100 Coverall: 0.632
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- - Map Face Shield: 0.1239
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- - Mar 100 Face Shield: 0.3861
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- - Map Gloves: 0.1038
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- - Mar 100 Gloves: 0.3379
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- - Map Goggles: 0.0372
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- - Mar 100 Goggles: 0.3092
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- - Map Mask: 0.2304
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  - Mar 100 Mask: 0.3876
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  ## Model description
@@ -58,37 +58,47 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 0.0001
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- - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: cosine
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- - num_epochs: 20
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Map | Map 50 | Map 75 | Map Small | Map Medium | Map Large | Mar 1 | Mar 10 | Mar 100 | Mar Small | Mar Medium | Mar Large | Map Coverall | Mar 100 Coverall | Map Face Shield | Mar 100 Face Shield | Map Gloves | Mar 100 Gloves | Map Goggles | Mar 100 Goggles | Map Mask | Mar 100 Mask |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:------------:|:----------------:|:---------------:|:-------------------:|:----------:|:--------------:|:-----------:|:---------------:|:--------:|:------------:|
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- | No log | 1.0 | 107 | 2.4345 | 0.0025 | 0.0117 | 0.0001 | 0.0031 | 0.0042 | 0.0014 | 0.0104 | 0.0384 | 0.0714 | 0.0336 | 0.0987 | 0.0523 | 0.0007 | 0.0856 | 0.0026 | 0.1076 | 0.0002 | 0.0308 | 0.0 | 0.0 | 0.0089 | 0.1329 |
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- | No log | 2.0 | 214 | 2.1177 | 0.0058 | 0.0186 | 0.0039 | 0.0029 | 0.0042 | 0.0104 | 0.0224 | 0.0799 | 0.1055 | 0.0656 | 0.1019 | 0.1304 | 0.0173 | 0.1644 | 0.0007 | 0.0367 | 0.0026 | 0.1063 | 0.0008 | 0.0492 | 0.0077 | 0.1711 |
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- | No log | 3.0 | 321 | 1.8639 | 0.0236 | 0.0653 | 0.0116 | 0.0025 | 0.014 | 0.027 | 0.0513 | 0.1213 | 0.1498 | 0.0563 | 0.119 | 0.1881 | 0.088 | 0.3297 | 0.0068 | 0.0595 | 0.0033 | 0.1415 | 0.0004 | 0.0092 | 0.0195 | 0.2089 |
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- | No log | 4.0 | 428 | 1.6789 | 0.0346 | 0.0803 | 0.0268 | 0.0064 | 0.0251 | 0.041 | 0.0747 | 0.1761 | 0.2189 | 0.0694 | 0.163 | 0.2987 | 0.1429 | 0.5486 | 0.0092 | 0.1291 | 0.003 | 0.1571 | 0.001 | 0.0369 | 0.017 | 0.2227 |
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- | 2.5173 | 5.0 | 535 | 1.6678 | 0.0414 | 0.1 | 0.0309 | 0.0123 | 0.0344 | 0.0556 | 0.1003 | 0.1985 | 0.2444 | 0.0932 | 0.197 | 0.3174 | 0.1336 | 0.4887 | 0.0332 | 0.2481 | 0.0064 | 0.1973 | 0.002 | 0.0369 | 0.0317 | 0.2511 |
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- | 2.5173 | 6.0 | 642 | 1.8747 | 0.0341 | 0.0891 | 0.0217 | 0.0074 | 0.0423 | 0.0392 | 0.0872 | 0.1979 | 0.2412 | 0.0691 | 0.1803 | 0.3318 | 0.0923 | 0.5198 | 0.0171 | 0.1911 | 0.0183 | 0.1826 | 0.0008 | 0.0985 | 0.0421 | 0.2138 |
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- | 2.5173 | 7.0 | 749 | 1.6153 | 0.0555 | 0.1413 | 0.0372 | 0.0126 | 0.0497 | 0.0812 | 0.1012 | 0.2199 | 0.255 | 0.1117 | 0.2002 | 0.3413 | 0.1711 | 0.5023 | 0.0311 | 0.1886 | 0.0234 | 0.1978 | 0.0019 | 0.1 | 0.0499 | 0.2862 |
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- | 2.5173 | 8.0 | 856 | 1.5458 | 0.085 | 0.207 | 0.0597 | 0.0218 | 0.0735 | 0.1101 | 0.1362 | 0.2698 | 0.3038 | 0.107 | 0.2324 | 0.4444 | 0.2387 | 0.5613 | 0.0491 | 0.2595 | 0.0393 | 0.2491 | 0.0051 | 0.1385 | 0.0926 | 0.3107 |
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- | 2.5173 | 9.0 | 963 | 1.4737 | 0.0998 | 0.2394 | 0.0738 | 0.0257 | 0.09 | 0.1373 | 0.1328 | 0.2961 | 0.3372 | 0.1365 | 0.286 | 0.4551 | 0.2987 | 0.5833 | 0.0463 | 0.2722 | 0.0393 | 0.2705 | 0.0093 | 0.2108 | 0.1055 | 0.3493 |
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- | 1.4606 | 10.0 | 1070 | 1.4459 | 0.1192 | 0.2641 | 0.0884 | 0.0249 | 0.1004 | 0.1666 | 0.1615 | 0.3041 | 0.3404 | 0.1114 | 0.2709 | 0.5104 | 0.3475 | 0.6045 | 0.0504 | 0.3051 | 0.0607 | 0.2603 | 0.0077 | 0.1785 | 0.1298 | 0.3538 |
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- | 1.4606 | 11.0 | 1177 | 1.4111 | 0.139 | 0.3108 | 0.106 | 0.0335 | 0.1135 | 0.1957 | 0.1748 | 0.3278 | 0.3602 | 0.1332 | 0.2968 | 0.5332 | 0.3809 | 0.6113 | 0.0683 | 0.3215 | 0.0676 | 0.2879 | 0.0069 | 0.24 | 0.1712 | 0.3404 |
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- | 1.4606 | 12.0 | 1284 | 1.3864 | 0.1518 | 0.3352 | 0.1224 | 0.0325 | 0.1291 | 0.2138 | 0.1757 | 0.3332 | 0.3674 | 0.1373 | 0.3102 | 0.521 | 0.4031 | 0.6167 | 0.0681 | 0.2937 | 0.0721 | 0.3013 | 0.0194 | 0.2615 | 0.1964 | 0.3636 |
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- | 1.4606 | 13.0 | 1391 | 1.3704 | 0.159 | 0.3398 | 0.1218 | 0.0382 | 0.1262 | 0.2277 | 0.1829 | 0.3494 | 0.3807 | 0.1273 | 0.3245 | 0.5416 | 0.4058 | 0.6243 | 0.0825 | 0.3582 | 0.0824 | 0.2969 | 0.0206 | 0.2569 | 0.2039 | 0.3671 |
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- | 1.4606 | 14.0 | 1498 | 1.3534 | 0.1553 | 0.3483 | 0.1227 | 0.0371 | 0.1157 | 0.2372 | 0.1878 | 0.3518 | 0.3822 | 0.1263 | 0.3257 | 0.5434 | 0.4125 | 0.6113 | 0.0796 | 0.3684 | 0.0846 | 0.3027 | 0.0137 | 0.2523 | 0.1863 | 0.3764 |
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- | 1.2325 | 15.0 | 1605 | 1.3488 | 0.1642 | 0.3747 | 0.1284 | 0.0514 | 0.1233 | 0.2522 | 0.1958 | 0.3479 | 0.378 | 0.1332 | 0.3223 | 0.5373 | 0.4146 | 0.5995 | 0.0956 | 0.3203 | 0.0784 | 0.2951 | 0.0295 | 0.3 | 0.203 | 0.3751 |
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- | 1.2325 | 16.0 | 1712 | 1.3200 | 0.1806 | 0.393 | 0.1471 | 0.0662 | 0.1429 | 0.2668 | 0.2091 | 0.367 | 0.3922 | 0.1413 | 0.3381 | 0.5545 | 0.424 | 0.6221 | 0.1245 | 0.3709 | 0.1015 | 0.3156 | 0.0293 | 0.2846 | 0.2234 | 0.368 |
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- | 1.2325 | 17.0 | 1819 | 1.3110 | 0.1825 | 0.391 | 0.1407 | 0.0665 | 0.149 | 0.2635 | 0.2116 | 0.3724 | 0.3998 | 0.1443 | 0.3565 | 0.5489 | 0.4204 | 0.6162 | 0.1207 | 0.3772 | 0.1011 | 0.329 | 0.0432 | 0.2954 | 0.2268 | 0.3813 |
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- | 1.2325 | 18.0 | 1926 | 1.2965 | 0.1859 | 0.3958 | 0.1484 | 0.0751 | 0.1529 | 0.2665 | 0.2154 | 0.3792 | 0.41 | 0.155 | 0.3626 | 0.559 | 0.4314 | 0.6279 | 0.1269 | 0.3975 | 0.1034 | 0.3321 | 0.0401 | 0.3169 | 0.2275 | 0.3756 |
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- | 1.1097 | 19.0 | 2033 | 1.2951 | 0.1859 | 0.3982 | 0.1491 | 0.075 | 0.1541 | 0.2661 | 0.2167 | 0.3814 | 0.4114 | 0.1527 | 0.3623 | 0.5655 | 0.4313 | 0.632 | 0.126 | 0.3937 | 0.1031 | 0.3362 | 0.0389 | 0.3138 | 0.2302 | 0.3813 |
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- | 1.1097 | 20.0 | 2140 | 1.2957 | 0.1854 | 0.3967 | 0.1509 | 0.075 | 0.1538 | 0.2634 | 0.2171 | 0.382 | 0.4106 | 0.1542 | 0.3591 | 0.5679 | 0.4319 | 0.632 | 0.1239 | 0.3861 | 0.1038 | 0.3379 | 0.0372 | 0.3092 | 0.2304 | 0.3876 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [microsoft/conditional-detr-resnet-50](https://huggingface.co/microsoft/conditional-detr-resnet-50) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.1948
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+ - Map: 0.2499
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+ - Map 50: 0.4967
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+ - Map 75: 0.2179
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+ - Map Small: 0.0841
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+ - Map Medium: 0.1886
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+ - Map Large: 0.3909
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+ - Mar 1: 0.2726
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+ - Mar 10: 0.4182
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+ - Mar 100: 0.4386
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+ - Mar Small: 0.19
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+ - Mar Medium: 0.3741
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+ - Mar Large: 0.6136
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+ - Map Coverall: 0.5025
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+ - Mar 100 Coverall: 0.6455
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+ - Map Face Shield: 0.1942
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+ - Mar 100 Face Shield: 0.4684
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+ - Map Gloves: 0.1747
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+ - Mar 100 Gloves: 0.3268
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+ - Map Goggles: 0.0966
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+ - Mar 100 Goggles: 0.3646
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+ - Map Mask: 0.2813
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  - Mar 100 Mask: 0.3876
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  ## Model description
 
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  The following hyperparameters were used during training:
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  - learning_rate: 0.0001
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+ - train_batch_size: 4
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  - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: cosine
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+ - num_epochs: 30
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Map | Map 50 | Map 75 | Map Small | Map Medium | Map Large | Mar 1 | Mar 10 | Mar 100 | Mar Small | Mar Medium | Mar Large | Map Coverall | Mar 100 Coverall | Map Face Shield | Mar 100 Face Shield | Map Gloves | Mar 100 Gloves | Map Goggles | Mar 100 Goggles | Map Mask | Mar 100 Mask |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:------------:|:----------------:|:---------------:|:-------------------:|:----------:|:--------------:|:-----------:|:---------------:|:--------:|:------------:|
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+ | No log | 1.0 | 213 | 1.6525 | 0.0703 | 0.2031 | 0.0433 | 0.0299 | 0.068 | 0.1001 | 0.1046 | 0.2461 | 0.2786 | 0.1027 | 0.2047 | 0.4363 | 0.1706 | 0.4932 | 0.0337 | 0.3101 | 0.031 | 0.1647 | 0.0228 | 0.2031 | 0.0933 | 0.2218 |
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+ | No log | 2.0 | 426 | 1.6502 | 0.0978 | 0.2478 | 0.0697 | 0.025 | 0.0751 | 0.1311 | 0.1301 | 0.2551 | 0.284 | 0.0961 | 0.2283 | 0.4022 | 0.283 | 0.5113 | 0.0412 | 0.2924 | 0.0296 | 0.1634 | 0.0063 | 0.1462 | 0.1289 | 0.3067 |
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+ | 1.4225 | 3.0 | 639 | 1.4811 | 0.1261 | 0.2915 | 0.1006 | 0.0252 | 0.0989 | 0.1814 | 0.1428 | 0.2983 | 0.3284 | 0.1349 | 0.2622 | 0.4458 | 0.3502 | 0.559 | 0.0573 | 0.3342 | 0.0481 | 0.2451 | 0.0318 | 0.1954 | 0.143 | 0.3084 |
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+ | 1.4225 | 4.0 | 852 | 1.5632 | 0.1139 | 0.2702 | 0.0806 | 0.0269 | 0.1017 | 0.161 | 0.1539 | 0.2913 | 0.3201 | 0.0927 | 0.2672 | 0.4895 | 0.3249 | 0.5423 | 0.0486 | 0.3747 | 0.0406 | 0.2196 | 0.012 | 0.18 | 0.1433 | 0.284 |
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+ | 1.3417 | 5.0 | 1065 | 1.4972 | 0.1367 | 0.3437 | 0.0837 | 0.0342 | 0.1207 | 0.2002 | 0.1662 | 0.3102 | 0.3398 | 0.1557 | 0.2827 | 0.4889 | 0.3526 | 0.5279 | 0.0926 | 0.3835 | 0.0575 | 0.2804 | 0.0225 | 0.2123 | 0.158 | 0.2947 |
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+ | 1.3417 | 6.0 | 1278 | 2.0791 | 0.0686 | 0.1679 | 0.0548 | 0.0159 | 0.0595 | 0.1028 | 0.1161 | 0.2163 | 0.24 | 0.0518 | 0.1646 | 0.3794 | 0.1974 | 0.4725 | 0.0306 | 0.2835 | 0.0132 | 0.1129 | 0.011 | 0.1215 | 0.0908 | 0.2093 |
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+ | 1.3417 | 7.0 | 1491 | 1.5761 | 0.1305 | 0.316 | 0.0907 | 0.0326 | 0.1104 | 0.1929 | 0.1635 | 0.2941 | 0.3186 | 0.0944 | 0.2729 | 0.4685 | 0.3526 | 0.5432 | 0.0669 | 0.338 | 0.0552 | 0.2237 | 0.0188 | 0.2154 | 0.1592 | 0.2729 |
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+ | 1.3563 | 8.0 | 1704 | 1.4740 | 0.1358 | 0.3298 | 0.1007 | 0.0481 | 0.0974 | 0.204 | 0.1764 | 0.3134 | 0.3385 | 0.1131 | 0.2699 | 0.4958 | 0.3837 | 0.5721 | 0.0467 | 0.3481 | 0.0714 | 0.2781 | 0.0247 | 0.2015 | 0.1525 | 0.2929 |
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+ | 1.3563 | 9.0 | 1917 | 1.3881 | 0.154 | 0.3402 | 0.1202 | 0.051 | 0.1001 | 0.2548 | 0.1965 | 0.3447 | 0.3688 | 0.1387 | 0.3017 | 0.5239 | 0.4029 | 0.577 | 0.0607 | 0.3987 | 0.0769 | 0.2817 | 0.0312 | 0.2492 | 0.1982 | 0.3373 |
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+ | 1.2296 | 10.0 | 2130 | 1.3749 | 0.1667 | 0.3709 | 0.1307 | 0.0451 | 0.1214 | 0.2496 | 0.2003 | 0.3456 | 0.3754 | 0.1741 | 0.3012 | 0.5318 | 0.4079 | 0.5815 | 0.0844 | 0.3785 | 0.0769 | 0.2786 | 0.0579 | 0.2877 | 0.2061 | 0.3507 |
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+ | 1.2296 | 11.0 | 2343 | 1.4515 | 0.1547 | 0.3413 | 0.1127 | 0.0501 | 0.1073 | 0.2393 | 0.1987 | 0.3446 | 0.3671 | 0.1278 | 0.2835 | 0.5541 | 0.4073 | 0.5937 | 0.075 | 0.3962 | 0.0841 | 0.2647 | 0.0353 | 0.2631 | 0.172 | 0.3178 |
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+ | 1.177 | 12.0 | 2556 | 1.3468 | 0.181 | 0.4023 | 0.1344 | 0.0671 | 0.1298 | 0.2793 | 0.2168 | 0.3708 | 0.3893 | 0.1484 | 0.3253 | 0.5562 | 0.4331 | 0.605 | 0.0705 | 0.4 | 0.1084 | 0.2937 | 0.0773 | 0.2985 | 0.2157 | 0.3493 |
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+ | 1.177 | 13.0 | 2769 | 1.3865 | 0.1825 | 0.403 | 0.1513 | 0.0671 | 0.1276 | 0.2829 | 0.2284 | 0.3638 | 0.3871 | 0.1364 | 0.3236 | 0.5426 | 0.4189 | 0.5761 | 0.1179 | 0.443 | 0.1034 | 0.2688 | 0.0411 | 0.2892 | 0.2313 | 0.3582 |
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+ | 1.177 | 14.0 | 2982 | 1.3681 | 0.1859 | 0.4196 | 0.1459 | 0.079 | 0.1364 | 0.2877 | 0.22 | 0.3575 | 0.3835 | 0.171 | 0.3239 | 0.5427 | 0.4364 | 0.5833 | 0.0954 | 0.4291 | 0.1286 | 0.2906 | 0.0354 | 0.2508 | 0.2336 | 0.3636 |
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+ | 1.1048 | 15.0 | 3195 | 1.3309 | 0.1951 | 0.437 | 0.1376 | 0.0694 | 0.1536 | 0.2885 | 0.2174 | 0.3772 | 0.4013 | 0.199 | 0.335 | 0.5492 | 0.4146 | 0.5788 | 0.1326 | 0.4544 | 0.1251 | 0.2924 | 0.0675 | 0.3108 | 0.2357 | 0.3702 |
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+ | 1.1048 | 16.0 | 3408 | 1.3157 | 0.1963 | 0.4285 | 0.1504 | 0.0752 | 0.1436 | 0.2995 | 0.223 | 0.3718 | 0.3963 | 0.1912 | 0.3302 | 0.5525 | 0.4634 | 0.623 | 0.1127 | 0.4354 | 0.1286 | 0.3013 | 0.0515 | 0.28 | 0.2254 | 0.3418 |
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+ | 1.0378 | 17.0 | 3621 | 1.2817 | 0.2106 | 0.4515 | 0.1639 | 0.059 | 0.1678 | 0.327 | 0.2464 | 0.393 | 0.4207 | 0.195 | 0.3702 | 0.5692 | 0.4629 | 0.6153 | 0.1338 | 0.4747 | 0.1541 | 0.2969 | 0.0579 | 0.3462 | 0.2446 | 0.3707 |
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+ | 1.0378 | 18.0 | 3834 | 1.2396 | 0.2215 | 0.4521 | 0.1853 | 0.0586 | 0.1775 | 0.3466 | 0.2417 | 0.4006 | 0.4233 | 0.1831 | 0.3741 | 0.5823 | 0.4736 | 0.6252 | 0.129 | 0.443 | 0.1588 | 0.3138 | 0.0751 | 0.3462 | 0.2708 | 0.388 |
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+ | 0.973 | 19.0 | 4047 | 1.2390 | 0.2256 | 0.4742 | 0.1722 | 0.0742 | 0.1771 | 0.3543 | 0.2487 | 0.4059 | 0.427 | 0.1696 | 0.366 | 0.6033 | 0.4692 | 0.6261 | 0.1567 | 0.4595 | 0.1612 | 0.3089 | 0.0769 | 0.3631 | 0.2641 | 0.3773 |
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+ | 0.973 | 20.0 | 4260 | 1.2513 | 0.2229 | 0.4666 | 0.1821 | 0.0742 | 0.1733 | 0.3411 | 0.2467 | 0.4001 | 0.4188 | 0.1782 | 0.3576 | 0.5939 | 0.4799 | 0.6248 | 0.1588 | 0.4418 | 0.166 | 0.3201 | 0.0554 | 0.3369 | 0.2545 | 0.3702 |
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+ | 0.973 | 21.0 | 4473 | 1.2462 | 0.22 | 0.4628 | 0.1884 | 0.0748 | 0.1663 | 0.3514 | 0.2475 | 0.3979 | 0.4187 | 0.1912 | 0.3486 | 0.5842 | 0.4785 | 0.6239 | 0.1633 | 0.4278 | 0.1561 | 0.3299 | 0.063 | 0.3338 | 0.2391 | 0.3782 |
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+ | 0.9176 | 22.0 | 4686 | 1.2267 | 0.2331 | 0.4786 | 0.1893 | 0.0767 | 0.1758 | 0.3701 | 0.2526 | 0.4064 | 0.4295 | 0.1776 | 0.3631 | 0.6074 | 0.4887 | 0.6351 | 0.1775 | 0.4532 | 0.1637 | 0.3223 | 0.0765 | 0.3492 | 0.259 | 0.3876 |
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+ | 0.9176 | 23.0 | 4899 | 1.2194 | 0.2424 | 0.4905 | 0.2118 | 0.0855 | 0.1845 | 0.3772 | 0.2661 | 0.4189 | 0.4374 | 0.1794 | 0.3724 | 0.6124 | 0.4932 | 0.6396 | 0.196 | 0.4684 | 0.1649 | 0.3147 | 0.0815 | 0.3677 | 0.2766 | 0.3964 |
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+ | 0.8635 | 24.0 | 5112 | 1.2143 | 0.2423 | 0.4878 | 0.2021 | 0.0835 | 0.1854 | 0.3895 | 0.2636 | 0.4119 | 0.4325 | 0.1917 | 0.3676 | 0.6119 | 0.4903 | 0.6369 | 0.1863 | 0.4582 | 0.1703 | 0.3281 | 0.0952 | 0.3554 | 0.2694 | 0.384 |
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+ | 0.8635 | 25.0 | 5325 | 1.2103 | 0.2503 | 0.5037 | 0.2134 | 0.0908 | 0.1879 | 0.3952 | 0.2681 | 0.4158 | 0.4339 | 0.1905 | 0.368 | 0.6105 | 0.4962 | 0.6405 | 0.2075 | 0.4658 | 0.1745 | 0.3232 | 0.1001 | 0.3508 | 0.2731 | 0.3893 |
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+ | 0.8281 | 26.0 | 5538 | 1.2096 | 0.2471 | 0.4963 | 0.2021 | 0.0874 | 0.1821 | 0.3923 | 0.2668 | 0.4153 | 0.4359 | 0.1913 | 0.3686 | 0.6179 | 0.4927 | 0.6347 | 0.1942 | 0.462 | 0.1682 | 0.3268 | 0.1019 | 0.3708 | 0.2783 | 0.3853 |
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+ | 0.8281 | 27.0 | 5751 | 1.2003 | 0.2479 | 0.4958 | 0.2114 | 0.0834 | 0.1861 | 0.3924 | 0.272 | 0.4205 | 0.4421 | 0.1837 | 0.3766 | 0.6251 | 0.5006 | 0.645 | 0.2003 | 0.4722 | 0.1674 | 0.3259 | 0.0912 | 0.3785 | 0.2798 | 0.3889 |
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+ | 0.8281 | 28.0 | 5964 | 1.1952 | 0.2488 | 0.4946 | 0.2172 | 0.084 | 0.1868 | 0.3898 | 0.2709 | 0.4182 | 0.4397 | 0.1878 | 0.3747 | 0.6173 | 0.5029 | 0.6473 | 0.1956 | 0.4709 | 0.171 | 0.3272 | 0.0942 | 0.3662 | 0.2805 | 0.3871 |
100
+ | 0.8017 | 29.0 | 6177 | 1.1944 | 0.2491 | 0.4937 | 0.2171 | 0.0832 | 0.1866 | 0.3916 | 0.272 | 0.4177 | 0.438 | 0.19 | 0.3721 | 0.6151 | 0.5025 | 0.645 | 0.1938 | 0.4684 | 0.173 | 0.3272 | 0.094 | 0.3615 | 0.282 | 0.388 |
101
+ | 0.8017 | 30.0 | 6390 | 1.1948 | 0.2499 | 0.4967 | 0.2179 | 0.0841 | 0.1886 | 0.3909 | 0.2726 | 0.4182 | 0.4386 | 0.19 | 0.3741 | 0.6136 | 0.5025 | 0.6455 | 0.1942 | 0.4684 | 0.1747 | 0.3268 | 0.0966 | 0.3646 | 0.2813 | 0.3876 |
102
 
103
 
104
  ### Framework versions
model.safetensors CHANGED
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  size 174079796
 
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