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tree-crown-latest

Image Classification
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vit
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  1. README.md +156 -156
  2. config.json +1 -1
  3. model.safetensors +1 -1
  4. training_args.bin +2 -2
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.95
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1368
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- - Accuracy: 0.95
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  ## Model description
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@@ -64,161 +64,161 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 17 | 2.0491 | 0.45 |
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- | No log | 2.0 | 34 | 1.7960 | 0.45 |
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- | No log | 3.0 | 51 | 1.6265 | 0.5 |
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- | No log | 4.0 | 68 | 1.4328 | 0.6 |
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- | No log | 5.0 | 85 | 1.3004 | 0.7 |
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- | No log | 6.0 | 102 | 1.1381 | 0.8 |
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- | No log | 7.0 | 119 | 1.0114 | 0.9 |
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- | No log | 8.0 | 136 | 0.9116 | 0.9 |
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- | No log | 9.0 | 153 | 0.8490 | 0.9 |
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- | No log | 10.0 | 170 | 0.7989 | 0.9 |
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- | No log | 11.0 | 187 | 0.7392 | 0.9 |
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- | No log | 12.0 | 204 | 0.6834 | 0.9 |
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- | No log | 13.0 | 221 | 0.6688 | 0.9 |
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- | No log | 14.0 | 238 | 0.6311 | 0.9 |
81
- | No log | 15.0 | 255 | 0.5847 | 0.9 |
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- | No log | 16.0 | 272 | 0.5544 | 0.9 |
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- | No log | 17.0 | 289 | 0.5521 | 0.9 |
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- | No log | 18.0 | 306 | 0.5319 | 0.9 |
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- | No log | 19.0 | 323 | 0.5228 | 0.9 |
86
- | No log | 20.0 | 340 | 0.4746 | 0.95 |
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- | No log | 21.0 | 357 | 0.4913 | 0.95 |
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- | No log | 22.0 | 374 | 0.4453 | 0.9 |
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- | No log | 23.0 | 391 | 0.4333 | 0.95 |
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- | No log | 24.0 | 408 | 0.4124 | 0.95 |
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- | No log | 25.0 | 425 | 0.4303 | 0.95 |
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- | No log | 26.0 | 442 | 0.4094 | 0.95 |
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- | No log | 27.0 | 459 | 0.3597 | 0.95 |
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- | No log | 28.0 | 476 | 0.3644 | 0.95 |
95
- | No log | 29.0 | 493 | 0.3723 | 0.95 |
96
- | 0.6158 | 30.0 | 510 | 0.3200 | 0.95 |
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- | 0.6158 | 31.0 | 527 | 0.3223 | 0.95 |
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- | 0.6158 | 32.0 | 544 | 0.3119 | 0.95 |
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- | 0.6158 | 33.0 | 561 | 0.3002 | 0.95 |
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- | 0.6158 | 34.0 | 578 | 0.2867 | 0.95 |
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- | 0.6158 | 35.0 | 595 | 0.3419 | 0.9 |
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- | 0.6158 | 36.0 | 612 | 0.3020 | 0.9 |
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- | 0.6158 | 37.0 | 629 | 0.2393 | 0.95 |
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- | 0.6158 | 38.0 | 646 | 0.3202 | 0.95 |
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- | 0.6158 | 39.0 | 663 | 0.2727 | 0.95 |
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- | 0.6158 | 40.0 | 680 | 0.2691 | 0.95 |
107
- | 0.6158 | 41.0 | 697 | 0.3346 | 0.9 |
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- | 0.6158 | 42.0 | 714 | 0.2446 | 0.95 |
109
- | 0.6158 | 43.0 | 731 | 0.3373 | 0.9 |
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- | 0.6158 | 44.0 | 748 | 0.2904 | 0.95 |
111
- | 0.6158 | 45.0 | 765 | 0.2307 | 0.95 |
112
- | 0.6158 | 46.0 | 782 | 0.2346 | 0.95 |
113
- | 0.6158 | 47.0 | 799 | 0.2314 | 0.95 |
114
- | 0.6158 | 48.0 | 816 | 0.2209 | 0.95 |
115
- | 0.6158 | 49.0 | 833 | 0.2233 | 0.95 |
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- | 0.6158 | 50.0 | 850 | 0.2225 | 0.95 |
117
- | 0.6158 | 51.0 | 867 | 0.2326 | 0.95 |
118
- | 0.6158 | 52.0 | 884 | 0.2233 | 0.95 |
119
- | 0.6158 | 53.0 | 901 | 0.2248 | 0.95 |
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- | 0.6158 | 54.0 | 918 | 0.2268 | 0.95 |
121
- | 0.6158 | 55.0 | 935 | 0.2130 | 0.95 |
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- | 0.6158 | 56.0 | 952 | 0.2164 | 0.95 |
123
- | 0.6158 | 57.0 | 969 | 0.1972 | 0.95 |
124
- | 0.6158 | 58.0 | 986 | 0.2374 | 0.95 |
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- | 0.1237 | 59.0 | 1003 | 0.2425 | 0.95 |
126
- | 0.1237 | 60.0 | 1020 | 0.1907 | 0.95 |
127
- | 0.1237 | 61.0 | 1037 | 0.3103 | 0.9 |
128
- | 0.1237 | 62.0 | 1054 | 0.2309 | 0.95 |
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- | 0.1237 | 63.0 | 1071 | 0.1982 | 0.95 |
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- | 0.1237 | 64.0 | 1088 | 0.2661 | 0.9 |
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- | 0.1237 | 65.0 | 1105 | 0.1739 | 0.95 |
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- | 0.1237 | 66.0 | 1122 | 0.1958 | 0.95 |
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- | 0.1237 | 67.0 | 1139 | 0.1729 | 0.95 |
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- | 0.1237 | 68.0 | 1156 | 0.1884 | 0.95 |
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- | 0.1237 | 69.0 | 1173 | 0.1958 | 0.95 |
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- | 0.1237 | 70.0 | 1190 | 0.1949 | 0.95 |
137
- | 0.1237 | 71.0 | 1207 | 0.1700 | 0.95 |
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- | 0.1237 | 72.0 | 1224 | 0.1770 | 0.95 |
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- | 0.1237 | 73.0 | 1241 | 0.1789 | 0.95 |
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- | 0.1237 | 74.0 | 1258 | 0.2202 | 0.95 |
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- | 0.1237 | 75.0 | 1275 | 0.2005 | 0.95 |
142
- | 0.1237 | 76.0 | 1292 | 0.1734 | 0.95 |
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- | 0.1237 | 77.0 | 1309 | 0.1633 | 0.95 |
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- | 0.1237 | 78.0 | 1326 | 0.1468 | 0.95 |
145
- | 0.1237 | 79.0 | 1343 | 0.1619 | 0.95 |
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- | 0.1237 | 80.0 | 1360 | 0.1706 | 0.95 |
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- | 0.1237 | 81.0 | 1377 | 0.1745 | 0.95 |
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- | 0.1237 | 82.0 | 1394 | 0.2146 | 0.95 |
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- | 0.1237 | 83.0 | 1411 | 0.1990 | 0.95 |
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- | 0.1237 | 84.0 | 1428 | 0.1682 | 0.95 |
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- | 0.1237 | 85.0 | 1445 | 0.1891 | 0.95 |
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- | 0.1237 | 86.0 | 1462 | 0.1646 | 0.95 |
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- | 0.1237 | 87.0 | 1479 | 0.2234 | 0.95 |
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- | 0.1237 | 88.0 | 1496 | 0.2469 | 0.9 |
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- | 0.0723 | 89.0 | 1513 | 0.1513 | 0.95 |
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- | 0.0723 | 90.0 | 1530 | 0.1638 | 0.95 |
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- | 0.0723 | 91.0 | 1547 | 0.1706 | 0.95 |
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- | 0.0723 | 92.0 | 1564 | 0.1578 | 0.95 |
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- | 0.0723 | 93.0 | 1581 | 0.1465 | 0.95 |
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- | 0.0723 | 94.0 | 1598 | 0.1433 | 0.95 |
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- | 0.0723 | 95.0 | 1615 | 0.1438 | 0.95 |
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- | 0.0723 | 96.0 | 1632 | 0.1543 | 0.95 |
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- | 0.0723 | 97.0 | 1649 | 0.1528 | 0.95 |
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- | 0.0723 | 98.0 | 1666 | 0.1807 | 0.95 |
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- | 0.0723 | 99.0 | 1683 | 0.2142 | 0.95 |
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- | 0.0723 | 100.0 | 1700 | 0.2056 | 0.95 |
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- | 0.0723 | 101.0 | 1717 | 0.1817 | 0.95 |
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- | 0.0723 | 102.0 | 1734 | 0.2271 | 0.95 |
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- | 0.0723 | 103.0 | 1751 | 0.2560 | 0.9 |
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- | 0.0723 | 104.0 | 1768 | 0.1631 | 0.95 |
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- | 0.0723 | 105.0 | 1785 | 0.1828 | 0.95 |
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- | 0.0723 | 106.0 | 1802 | 0.2608 | 0.95 |
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- | 0.0723 | 107.0 | 1819 | 0.2562 | 0.95 |
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- | 0.0723 | 108.0 | 1836 | 0.1666 | 0.95 |
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- | 0.0723 | 109.0 | 1853 | 0.1619 | 0.95 |
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- | 0.0723 | 110.0 | 1870 | 0.1504 | 0.95 |
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- | 0.0723 | 111.0 | 1887 | 0.1433 | 0.95 |
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- | 0.0723 | 112.0 | 1904 | 0.1457 | 0.95 |
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- | 0.0723 | 113.0 | 1921 | 0.1288 | 1.0 |
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- | 0.0723 | 114.0 | 1938 | 0.1401 | 1.0 |
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- | 0.0723 | 115.0 | 1955 | 0.1281 | 0.95 |
182
- | 0.0723 | 116.0 | 1972 | 0.1267 | 0.95 |
183
- | 0.0723 | 117.0 | 1989 | 0.1288 | 0.95 |
184
- | 0.051 | 118.0 | 2006 | 0.1473 | 0.95 |
185
- | 0.051 | 119.0 | 2023 | 0.1106 | 1.0 |
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- | 0.051 | 120.0 | 2040 | 0.1097 | 1.0 |
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- | 0.051 | 121.0 | 2057 | 0.1379 | 1.0 |
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- | 0.051 | 122.0 | 2074 | 0.1347 | 1.0 |
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- | 0.051 | 123.0 | 2091 | 0.1302 | 0.95 |
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- | 0.051 | 124.0 | 2108 | 0.1599 | 0.95 |
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- | 0.051 | 125.0 | 2125 | 0.1574 | 0.95 |
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- | 0.051 | 126.0 | 2142 | 0.1541 | 0.95 |
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- | 0.051 | 127.0 | 2159 | 0.1517 | 0.95 |
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- | 0.051 | 128.0 | 2176 | 0.1462 | 0.95 |
195
- | 0.051 | 129.0 | 2193 | 0.1574 | 0.95 |
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- | 0.051 | 130.0 | 2210 | 0.1598 | 0.95 |
197
- | 0.051 | 131.0 | 2227 | 0.1520 | 0.95 |
198
- | 0.051 | 132.0 | 2244 | 0.1595 | 0.95 |
199
- | 0.051 | 133.0 | 2261 | 0.1555 | 0.95 |
200
- | 0.051 | 134.0 | 2278 | 0.1515 | 0.95 |
201
- | 0.051 | 135.0 | 2295 | 0.1686 | 0.95 |
202
- | 0.051 | 136.0 | 2312 | 0.1670 | 0.95 |
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- | 0.051 | 137.0 | 2329 | 0.1533 | 0.95 |
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- | 0.051 | 138.0 | 2346 | 0.1472 | 0.95 |
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- | 0.051 | 139.0 | 2363 | 0.1530 | 0.95 |
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- | 0.051 | 140.0 | 2380 | 0.1563 | 0.95 |
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- | 0.051 | 141.0 | 2397 | 0.1500 | 0.95 |
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- | 0.051 | 142.0 | 2414 | 0.1462 | 0.95 |
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- | 0.051 | 143.0 | 2431 | 0.1432 | 0.95 |
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- | 0.051 | 144.0 | 2448 | 0.1417 | 0.95 |
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- | 0.051 | 145.0 | 2465 | 0.1414 | 0.95 |
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- | 0.051 | 146.0 | 2482 | 0.1362 | 0.95 |
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- | 0.051 | 147.0 | 2499 | 0.1358 | 0.95 |
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- | 0.0491 | 148.0 | 2516 | 0.1366 | 0.95 |
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- | 0.0491 | 149.0 | 2533 | 0.1367 | 0.95 |
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- | 0.0491 | 150.0 | 2550 | 0.1368 | 0.95 |
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  ### Framework versions
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- - Transformers 4.40.2
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- - Pytorch 2.2.1+cu121
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- - Datasets 2.19.1
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  - Tokenizers 0.19.1
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.8636363636363636
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  ---
27
 
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6589
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+ - Accuracy: 0.8636
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 36 | 1.5994 | 0.6364 |
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+ | No log | 2.0 | 72 | 1.2587 | 0.6818 |
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+ | No log | 3.0 | 108 | 1.0993 | 0.7045 |
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+ | No log | 4.0 | 144 | 0.9721 | 0.7955 |
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+ | No log | 5.0 | 180 | 0.9282 | 0.7955 |
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+ | No log | 6.0 | 216 | 0.8947 | 0.7955 |
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+ | No log | 7.0 | 252 | 0.8858 | 0.7727 |
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+ | No log | 8.0 | 288 | 0.8159 | 0.7955 |
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+ | No log | 9.0 | 324 | 0.7772 | 0.7727 |
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+ | No log | 10.0 | 360 | 0.7519 | 0.7955 |
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+ | No log | 11.0 | 396 | 0.6982 | 0.7955 |
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+ | No log | 12.0 | 432 | 0.6639 | 0.7955 |
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+ | No log | 13.0 | 468 | 0.6690 | 0.8409 |
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+ | 0.6601 | 14.0 | 504 | 0.6565 | 0.8409 |
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+ | 0.6601 | 15.0 | 540 | 0.6401 | 0.8409 |
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+ | 0.6601 | 16.0 | 576 | 0.5868 | 0.8864 |
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+ | 0.6601 | 17.0 | 612 | 0.5840 | 0.8864 |
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+ | 0.6601 | 18.0 | 648 | 0.6214 | 0.8409 |
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+ | 0.6601 | 19.0 | 684 | 0.6447 | 0.8636 |
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+ | 0.6601 | 20.0 | 720 | 0.6387 | 0.8409 |
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+ | 0.6601 | 21.0 | 756 | 0.5714 | 0.8636 |
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+ | 0.6601 | 22.0 | 792 | 0.5483 | 0.8864 |
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+ | 0.6601 | 23.0 | 828 | 0.5600 | 0.8864 |
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+ | 0.6601 | 24.0 | 864 | 0.5785 | 0.8864 |
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+ | 0.6601 | 25.0 | 900 | 0.5806 | 0.8864 |
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+ | 0.6601 | 26.0 | 936 | 0.5598 | 0.8636 |
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+ | 0.6601 | 27.0 | 972 | 0.5549 | 0.8864 |
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+ | 0.1909 | 28.0 | 1008 | 0.5145 | 0.8864 |
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+ | 0.1909 | 29.0 | 1044 | 0.5294 | 0.8636 |
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+ | 0.1909 | 30.0 | 1080 | 0.5846 | 0.8636 |
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+ | 0.1909 | 31.0 | 1116 | 0.5347 | 0.8864 |
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+ | 0.1909 | 32.0 | 1152 | 0.5251 | 0.8864 |
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+ | 0.1909 | 33.0 | 1188 | 0.5193 | 0.8864 |
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+ | 0.1909 | 34.0 | 1224 | 0.6406 | 0.8409 |
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+ | 0.1909 | 35.0 | 1260 | 0.5039 | 0.8864 |
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+ | 0.1909 | 36.0 | 1296 | 0.5137 | 0.8864 |
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+ | 0.1909 | 37.0 | 1332 | 0.6023 | 0.8636 |
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+ | 0.1909 | 38.0 | 1368 | 0.5625 | 0.8864 |
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+ | 0.1909 | 39.0 | 1404 | 0.5752 | 0.8864 |
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+ | 0.1909 | 40.0 | 1440 | 0.5903 | 0.8864 |
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+ | 0.1909 | 41.0 | 1476 | 0.5143 | 0.8864 |
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+ | 0.0968 | 42.0 | 1512 | 0.5261 | 0.8864 |
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+ | 0.0968 | 43.0 | 1548 | 0.5942 | 0.8864 |
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+ | 0.0968 | 44.0 | 1584 | 0.6026 | 0.8636 |
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+ | 0.0968 | 45.0 | 1620 | 0.5638 | 0.8864 |
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+ | 0.0968 | 46.0 | 1656 | 0.6019 | 0.8864 |
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+ | 0.0968 | 47.0 | 1692 | 0.5953 | 0.8864 |
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+ | 0.0968 | 48.0 | 1728 | 0.6043 | 0.8864 |
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+ | 0.0968 | 49.0 | 1764 | 0.5866 | 0.8864 |
116
+ | 0.0968 | 50.0 | 1800 | 0.5090 | 0.8864 |
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+ | 0.0968 | 51.0 | 1836 | 0.5704 | 0.8864 |
118
+ | 0.0968 | 52.0 | 1872 | 0.5579 | 0.8636 |
119
+ | 0.0968 | 53.0 | 1908 | 0.5058 | 0.8864 |
120
+ | 0.0968 | 54.0 | 1944 | 0.5418 | 0.8864 |
121
+ | 0.0968 | 55.0 | 1980 | 0.5708 | 0.8864 |
122
+ | 0.0656 | 56.0 | 2016 | 0.5818 | 0.8864 |
123
+ | 0.0656 | 57.0 | 2052 | 0.5539 | 0.8864 |
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+ | 0.0656 | 58.0 | 2088 | 0.5849 | 0.8864 |
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+ | 0.0656 | 59.0 | 2124 | 0.5396 | 0.8864 |
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+ | 0.0656 | 60.0 | 2160 | 0.5631 | 0.8864 |
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+ | 0.0656 | 61.0 | 2196 | 0.5919 | 0.8864 |
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+ | 0.0656 | 62.0 | 2232 | 0.5955 | 0.8864 |
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+ | 0.0656 | 63.0 | 2268 | 0.5438 | 0.8864 |
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+ | 0.0656 | 64.0 | 2304 | 0.5989 | 0.8636 |
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+ | 0.0656 | 65.0 | 2340 | 0.5062 | 0.8864 |
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+ | 0.0656 | 66.0 | 2376 | 0.5820 | 0.8636 |
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+ | 0.0656 | 67.0 | 2412 | 0.5301 | 0.8864 |
134
+ | 0.0656 | 68.0 | 2448 | 0.6138 | 0.8864 |
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+ | 0.0656 | 69.0 | 2484 | 0.5710 | 0.8636 |
136
+ | 0.0491 | 70.0 | 2520 | 0.6141 | 0.8636 |
137
+ | 0.0491 | 71.0 | 2556 | 0.6304 | 0.8636 |
138
+ | 0.0491 | 72.0 | 2592 | 0.5568 | 0.8636 |
139
+ | 0.0491 | 73.0 | 2628 | 0.6437 | 0.8636 |
140
+ | 0.0491 | 74.0 | 2664 | 0.5329 | 0.8864 |
141
+ | 0.0491 | 75.0 | 2700 | 0.6453 | 0.8864 |
142
+ | 0.0491 | 76.0 | 2736 | 0.6267 | 0.8636 |
143
+ | 0.0491 | 77.0 | 2772 | 0.6246 | 0.8636 |
144
+ | 0.0491 | 78.0 | 2808 | 0.6408 | 0.8636 |
145
+ | 0.0491 | 79.0 | 2844 | 0.6208 | 0.8636 |
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+ | 0.0491 | 80.0 | 2880 | 0.5944 | 0.8636 |
147
+ | 0.0491 | 81.0 | 2916 | 0.6848 | 0.8636 |
148
+ | 0.0491 | 82.0 | 2952 | 0.6700 | 0.8409 |
149
+ | 0.0491 | 83.0 | 2988 | 0.5625 | 0.8864 |
150
+ | 0.0474 | 84.0 | 3024 | 0.4997 | 0.8864 |
151
+ | 0.0474 | 85.0 | 3060 | 0.6110 | 0.8864 |
152
+ | 0.0474 | 86.0 | 3096 | 0.5661 | 0.8864 |
153
+ | 0.0474 | 87.0 | 3132 | 0.5681 | 0.8864 |
154
+ | 0.0474 | 88.0 | 3168 | 0.5794 | 0.8636 |
155
+ | 0.0474 | 89.0 | 3204 | 0.6098 | 0.8864 |
156
+ | 0.0474 | 90.0 | 3240 | 0.6009 | 0.8636 |
157
+ | 0.0474 | 91.0 | 3276 | 0.5000 | 0.8864 |
158
+ | 0.0474 | 92.0 | 3312 | 0.5285 | 0.8864 |
159
+ | 0.0474 | 93.0 | 3348 | 0.5774 | 0.8864 |
160
+ | 0.0474 | 94.0 | 3384 | 0.5896 | 0.8864 |
161
+ | 0.0474 | 95.0 | 3420 | 0.5478 | 0.8864 |
162
+ | 0.0474 | 96.0 | 3456 | 0.5815 | 0.8864 |
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+ | 0.0474 | 97.0 | 3492 | 0.5675 | 0.8864 |
164
+ | 0.0393 | 98.0 | 3528 | 0.5773 | 0.8864 |
165
+ | 0.0393 | 99.0 | 3564 | 0.6099 | 0.8864 |
166
+ | 0.0393 | 100.0 | 3600 | 0.7255 | 0.8409 |
167
+ | 0.0393 | 101.0 | 3636 | 0.6300 | 0.8864 |
168
+ | 0.0393 | 102.0 | 3672 | 0.5979 | 0.8409 |
169
+ | 0.0393 | 103.0 | 3708 | 0.6031 | 0.8864 |
170
+ | 0.0393 | 104.0 | 3744 | 0.6200 | 0.8864 |
171
+ | 0.0393 | 105.0 | 3780 | 0.6120 | 0.8864 |
172
+ | 0.0393 | 106.0 | 3816 | 0.5514 | 0.9091 |
173
+ | 0.0393 | 107.0 | 3852 | 0.6425 | 0.8864 |
174
+ | 0.0393 | 108.0 | 3888 | 0.6152 | 0.8864 |
175
+ | 0.0393 | 109.0 | 3924 | 0.6023 | 0.8864 |
176
+ | 0.0393 | 110.0 | 3960 | 0.6170 | 0.8864 |
177
+ | 0.0393 | 111.0 | 3996 | 0.6556 | 0.8864 |
178
+ | 0.0404 | 112.0 | 4032 | 0.6380 | 0.8864 |
179
+ | 0.0404 | 113.0 | 4068 | 0.6216 | 0.8864 |
180
+ | 0.0404 | 114.0 | 4104 | 0.5775 | 0.8864 |
181
+ | 0.0404 | 115.0 | 4140 | 0.6120 | 0.8864 |
182
+ | 0.0404 | 116.0 | 4176 | 0.6221 | 0.8864 |
183
+ | 0.0404 | 117.0 | 4212 | 0.6807 | 0.8636 |
184
+ | 0.0404 | 118.0 | 4248 | 0.6805 | 0.8636 |
185
+ | 0.0404 | 119.0 | 4284 | 0.6660 | 0.8636 |
186
+ | 0.0404 | 120.0 | 4320 | 0.6626 | 0.8636 |
187
+ | 0.0404 | 121.0 | 4356 | 0.6656 | 0.8636 |
188
+ | 0.0404 | 122.0 | 4392 | 0.6151 | 0.8636 |
189
+ | 0.0404 | 123.0 | 4428 | 0.6525 | 0.8636 |
190
+ | 0.0404 | 124.0 | 4464 | 0.6311 | 0.8636 |
191
+ | 0.0268 | 125.0 | 4500 | 0.6375 | 0.8636 |
192
+ | 0.0268 | 126.0 | 4536 | 0.6252 | 0.8636 |
193
+ | 0.0268 | 127.0 | 4572 | 0.6182 | 0.8409 |
194
+ | 0.0268 | 128.0 | 4608 | 0.6195 | 0.8636 |
195
+ | 0.0268 | 129.0 | 4644 | 0.6417 | 0.8636 |
196
+ | 0.0268 | 130.0 | 4680 | 0.6440 | 0.8636 |
197
+ | 0.0268 | 131.0 | 4716 | 0.6726 | 0.8636 |
198
+ | 0.0268 | 132.0 | 4752 | 0.6781 | 0.8636 |
199
+ | 0.0268 | 133.0 | 4788 | 0.6412 | 0.8636 |
200
+ | 0.0268 | 134.0 | 4824 | 0.6514 | 0.8636 |
201
+ | 0.0268 | 135.0 | 4860 | 0.6452 | 0.8636 |
202
+ | 0.0268 | 136.0 | 4896 | 0.6453 | 0.8864 |
203
+ | 0.0268 | 137.0 | 4932 | 0.6408 | 0.8864 |
204
+ | 0.0268 | 138.0 | 4968 | 0.6461 | 0.8864 |
205
+ | 0.0244 | 139.0 | 5004 | 0.6597 | 0.8864 |
206
+ | 0.0244 | 140.0 | 5040 | 0.6539 | 0.8864 |
207
+ | 0.0244 | 141.0 | 5076 | 0.6415 | 0.8864 |
208
+ | 0.0244 | 142.0 | 5112 | 0.6438 | 0.8864 |
209
+ | 0.0244 | 143.0 | 5148 | 0.6581 | 0.8636 |
210
+ | 0.0244 | 144.0 | 5184 | 0.6570 | 0.8636 |
211
+ | 0.0244 | 145.0 | 5220 | 0.6626 | 0.8636 |
212
+ | 0.0244 | 146.0 | 5256 | 0.6622 | 0.8636 |
213
+ | 0.0244 | 147.0 | 5292 | 0.6647 | 0.8636 |
214
+ | 0.0244 | 148.0 | 5328 | 0.6619 | 0.8636 |
215
+ | 0.0244 | 149.0 | 5364 | 0.6591 | 0.8636 |
216
+ | 0.0244 | 150.0 | 5400 | 0.6589 | 0.8636 |
217
 
218
 
219
  ### Framework versions
220
 
221
+ - Transformers 4.41.2
222
+ - Pytorch 2.3.0+cu121
223
+ - Datasets 2.20.0
224
  - Tokenizers 0.19.1
config.json CHANGED
@@ -44,5 +44,5 @@
44
  "problem_type": "single_label_classification",
45
  "qkv_bias": true,
46
  "torch_dtype": "float32",
47
- "transformers_version": "4.40.2"
48
  }
 
44
  "problem_type": "single_label_classification",
45
  "qkv_bias": true,
46
  "torch_dtype": "float32",
47
+ "transformers_version": "4.41.2"
48
  }
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