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Token Classification
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Safetensors
bert
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@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0015
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- - Precision: 1.0
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- - Recall: 1.0
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- - F1: 1.0
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- - Accuracy: 1.0
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  ## Model description
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@@ -55,106 +55,106 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | No log | 1.0 | 27 | 0.1989 | 0.0 | 0.0 | 0.0 | 0.9989 |
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- | No log | 2.0 | 54 | 0.1611 | 0.0 | 0.0 | 0.0 | 0.9989 |
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- | No log | 3.0 | 81 | 0.1334 | 0.0 | 0.0 | 0.0 | 0.9989 |
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- | No log | 4.0 | 108 | 0.1116 | 0.0 | 0.0 | 0.0 | 0.9989 |
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- | No log | 5.0 | 135 | 0.0943 | 0.0 | 0.0 | 0.0 | 0.9989 |
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- | No log | 6.0 | 162 | 0.0804 | 0.0 | 0.0 | 0.0 | 0.9989 |
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- | No log | 7.0 | 189 | 0.0692 | 0.0 | 0.0 | 0.0 | 0.9989 |
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- | No log | 8.0 | 216 | 0.0602 | 0.0 | 0.0 | 0.0 | 0.9989 |
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- | No log | 9.0 | 243 | 0.0528 | 0.0 | 0.0 | 0.0 | 0.9989 |
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- | No log | 10.0 | 270 | 0.0468 | 0.0 | 0.0 | 0.0 | 0.9989 |
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- | No log | 11.0 | 297 | 0.0418 | 0.0 | 0.0 | 0.0 | 0.9989 |
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- | No log | 12.0 | 324 | 0.0376 | 0.0 | 0.0 | 0.0 | 0.9989 |
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- | No log | 13.0 | 351 | 0.0341 | 0.0 | 0.0 | 0.0 | 0.9989 |
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- | No log | 14.0 | 378 | 0.0312 | 0.0 | 0.0 | 0.0 | 0.9989 |
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- | No log | 15.0 | 405 | 0.0287 | 0.0 | 0.0 | 0.0 | 0.9989 |
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- | No log | 16.0 | 432 | 0.0266 | 0.0 | 0.0 | 0.0 | 0.9989 |
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- | No log | 17.0 | 459 | 0.0247 | 0.0 | 0.0 | 0.0 | 0.9989 |
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- | No log | 18.0 | 486 | 0.0236 | 0.0 | 0.0 | 0.0 | 0.9989 |
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- | 0.0904 | 19.0 | 513 | 0.0218 | 0.0 | 0.0 | 0.0 | 0.9989 |
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- | 0.0904 | 20.0 | 540 | 0.0203 | 0.0 | 0.0 | 0.0 | 0.9989 |
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- | 0.0904 | 21.0 | 567 | 0.0156 | 0.8571 | 0.8571 | 0.8571 | 0.9997 |
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- | 0.0904 | 22.0 | 594 | 0.0142 | 1.0 | 0.8571 | 0.9231 | 0.9998 |
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- | 0.0904 | 23.0 | 621 | 0.0133 | 1.0 | 0.8571 | 0.9231 | 0.9998 |
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- | 0.0904 | 24.0 | 648 | 0.0122 | 1.0 | 0.8571 | 0.9231 | 0.9998 |
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- | 0.0904 | 25.0 | 675 | 0.0107 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0904 | 26.0 | 702 | 0.0099 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0904 | 27.0 | 729 | 0.0092 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0904 | 28.0 | 756 | 0.0086 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0904 | 29.0 | 783 | 0.0081 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0904 | 30.0 | 810 | 0.0076 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0904 | 31.0 | 837 | 0.0074 | 1.0 | 1.0 | 1.0 | 0.9998 |
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- | 0.0904 | 32.0 | 864 | 0.0073 | 1.0 | 0.8571 | 0.9231 | 0.9998 |
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- | 0.0904 | 33.0 | 891 | 0.0064 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0904 | 34.0 | 918 | 0.0061 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0904 | 35.0 | 945 | 0.0058 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0904 | 36.0 | 972 | 0.0055 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0904 | 37.0 | 999 | 0.0053 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0122 | 38.0 | 1026 | 0.0050 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0122 | 39.0 | 1053 | 0.0048 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0122 | 40.0 | 1080 | 0.0046 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0122 | 41.0 | 1107 | 0.0044 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0122 | 42.0 | 1134 | 0.0042 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0122 | 43.0 | 1161 | 0.0041 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0122 | 44.0 | 1188 | 0.0039 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0122 | 45.0 | 1215 | 0.0038 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0122 | 46.0 | 1242 | 0.0036 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0122 | 47.0 | 1269 | 0.0035 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0122 | 48.0 | 1296 | 0.0034 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0122 | 49.0 | 1323 | 0.0033 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0122 | 50.0 | 1350 | 0.0032 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0122 | 51.0 | 1377 | 0.0031 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0122 | 52.0 | 1404 | 0.0030 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0122 | 53.0 | 1431 | 0.0029 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0122 | 54.0 | 1458 | 0.0029 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0122 | 55.0 | 1485 | 0.0028 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0042 | 56.0 | 1512 | 0.0027 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0042 | 57.0 | 1539 | 0.0026 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0042 | 58.0 | 1566 | 0.0026 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0042 | 59.0 | 1593 | 0.0025 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0042 | 60.0 | 1620 | 0.0024 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0042 | 61.0 | 1647 | 0.0024 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0042 | 62.0 | 1674 | 0.0023 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0042 | 63.0 | 1701 | 0.0023 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0042 | 64.0 | 1728 | 0.0022 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0042 | 65.0 | 1755 | 0.0022 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0042 | 66.0 | 1782 | 0.0021 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0042 | 67.0 | 1809 | 0.0021 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0042 | 68.0 | 1836 | 0.0021 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0042 | 69.0 | 1863 | 0.0020 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0042 | 70.0 | 1890 | 0.0020 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0042 | 71.0 | 1917 | 0.0020 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0042 | 72.0 | 1944 | 0.0019 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0042 | 73.0 | 1971 | 0.0019 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0042 | 74.0 | 1998 | 0.0019 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0025 | 75.0 | 2025 | 0.0018 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0025 | 76.0 | 2052 | 0.0018 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0025 | 77.0 | 2079 | 0.0018 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0025 | 78.0 | 2106 | 0.0018 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0025 | 79.0 | 2133 | 0.0017 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0025 | 80.0 | 2160 | 0.0017 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0025 | 81.0 | 2187 | 0.0017 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0025 | 82.0 | 2214 | 0.0017 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0025 | 83.0 | 2241 | 0.0017 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0025 | 84.0 | 2268 | 0.0016 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0025 | 85.0 | 2295 | 0.0016 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0025 | 86.0 | 2322 | 0.0016 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0025 | 87.0 | 2349 | 0.0016 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0025 | 88.0 | 2376 | 0.0016 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0025 | 89.0 | 2403 | 0.0016 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0025 | 90.0 | 2430 | 0.0016 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0025 | 91.0 | 2457 | 0.0016 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0025 | 92.0 | 2484 | 0.0016 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0019 | 93.0 | 2511 | 0.0016 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0019 | 94.0 | 2538 | 0.0016 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0019 | 95.0 | 2565 | 0.0015 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0019 | 96.0 | 2592 | 0.0015 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0019 | 97.0 | 2619 | 0.0015 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0019 | 98.0 | 2646 | 0.0015 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0019 | 99.0 | 2673 | 0.0015 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0019 | 100.0 | 2700 | 0.0015 | 1.0 | 1.0 | 1.0 | 1.0 |
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  ### Framework versions
 
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21
  This model is a fine-tuned version of [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0336
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+ - Precision: 0.9730
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+ - Recall: 0.9789
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+ - F1: 0.9759
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+ - Accuracy: 0.9937
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 26 | 0.2470 | 0.7608 | 0.8733 | 0.8132 | 0.9776 |
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+ | No log | 2.0 | 52 | 0.1881 | 0.7803 | 0.8733 | 0.8242 | 0.9817 |
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+ | No log | 3.0 | 78 | 0.1495 | 0.9629 | 0.9789 | 0.9708 | 0.9929 |
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+ | No log | 4.0 | 104 | 0.1277 | 0.9744 | 0.9759 | 0.9751 | 0.9942 |
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+ | No log | 5.0 | 130 | 0.1107 | 0.9745 | 0.9804 | 0.9774 | 0.9949 |
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+ | No log | 6.0 | 156 | 0.1004 | 0.9688 | 0.9819 | 0.9753 | 0.9940 |
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+ | No log | 7.0 | 182 | 0.0895 | 0.9701 | 0.9804 | 0.9752 | 0.9942 |
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+ | No log | 8.0 | 208 | 0.0808 | 0.9745 | 0.9789 | 0.9767 | 0.9949 |
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+ | No log | 9.0 | 234 | 0.0731 | 0.9744 | 0.9774 | 0.9759 | 0.9947 |
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+ | No log | 10.0 | 260 | 0.0720 | 0.9731 | 0.9819 | 0.9775 | 0.9939 |
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+ | No log | 11.0 | 286 | 0.0662 | 0.9731 | 0.9819 | 0.9775 | 0.9940 |
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+ | No log | 12.0 | 312 | 0.0589 | 0.9804 | 0.9804 | 0.9804 | 0.9955 |
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+ | No log | 13.0 | 338 | 0.0573 | 0.9746 | 0.9819 | 0.9782 | 0.9945 |
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+ | No log | 14.0 | 364 | 0.0520 | 0.9789 | 0.9789 | 0.9789 | 0.9945 |
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+ | No log | 15.0 | 390 | 0.0507 | 0.9803 | 0.9774 | 0.9789 | 0.9947 |
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+ | No log | 16.0 | 416 | 0.0475 | 0.9804 | 0.9789 | 0.9796 | 0.9949 |
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+ | No log | 17.0 | 442 | 0.0461 | 0.9731 | 0.9804 | 0.9767 | 0.9944 |
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+ | No log | 18.0 | 468 | 0.0435 | 0.9773 | 0.9744 | 0.9758 | 0.9947 |
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+ | No log | 19.0 | 494 | 0.0400 | 0.9760 | 0.9819 | 0.9789 | 0.9952 |
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+ | 0.1028 | 20.0 | 520 | 0.0390 | 0.9834 | 0.9819 | 0.9826 | 0.9960 |
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+ | 0.1028 | 21.0 | 546 | 0.0386 | 0.9716 | 0.9804 | 0.9760 | 0.9945 |
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+ | 0.1028 | 22.0 | 572 | 0.0373 | 0.9688 | 0.9834 | 0.9760 | 0.9942 |
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+ | 0.1028 | 23.0 | 598 | 0.0355 | 0.9789 | 0.9804 | 0.9797 | 0.9950 |
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+ | 0.1028 | 24.0 | 624 | 0.0381 | 0.9617 | 0.9834 | 0.9724 | 0.9924 |
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+ | 0.1028 | 25.0 | 650 | 0.0328 | 0.9775 | 0.9819 | 0.9797 | 0.9950 |
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+ | 0.1028 | 26.0 | 676 | 0.0329 | 0.9789 | 0.9804 | 0.9797 | 0.9952 |
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+ | 0.1028 | 27.0 | 702 | 0.0357 | 0.9789 | 0.9804 | 0.9797 | 0.9950 |
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+ | 0.1028 | 28.0 | 728 | 0.0357 | 0.9688 | 0.9849 | 0.9768 | 0.9940 |
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+ | 0.1028 | 29.0 | 754 | 0.0382 | 0.9632 | 0.9864 | 0.9747 | 0.9921 |
87
+ | 0.1028 | 30.0 | 780 | 0.0303 | 0.9789 | 0.9819 | 0.9804 | 0.9953 |
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+ | 0.1028 | 31.0 | 806 | 0.0289 | 0.9819 | 0.9819 | 0.9819 | 0.9957 |
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+ | 0.1028 | 32.0 | 832 | 0.0296 | 0.9790 | 0.9834 | 0.9812 | 0.9955 |
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+ | 0.1028 | 33.0 | 858 | 0.0290 | 0.9848 | 0.9789 | 0.9818 | 0.9953 |
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+ | 0.1028 | 34.0 | 884 | 0.0301 | 0.9789 | 0.9819 | 0.9804 | 0.9953 |
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+ | 0.1028 | 35.0 | 910 | 0.0294 | 0.9702 | 0.9834 | 0.9768 | 0.9944 |
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+ | 0.1028 | 36.0 | 936 | 0.0347 | 0.9717 | 0.9834 | 0.9775 | 0.9936 |
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+ | 0.1028 | 37.0 | 962 | 0.0303 | 0.9746 | 0.9819 | 0.9782 | 0.9939 |
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+ | 0.1028 | 38.0 | 988 | 0.0344 | 0.9645 | 0.9849 | 0.9746 | 0.9923 |
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+ | 0.0209 | 39.0 | 1014 | 0.0300 | 0.9717 | 0.9834 | 0.9775 | 0.9937 |
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+ | 0.0209 | 40.0 | 1040 | 0.0288 | 0.9789 | 0.9819 | 0.9804 | 0.9950 |
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+ | 0.0209 | 41.0 | 1066 | 0.0289 | 0.9804 | 0.9819 | 0.9812 | 0.9952 |
99
+ | 0.0209 | 42.0 | 1092 | 0.0296 | 0.9716 | 0.9804 | 0.9760 | 0.9939 |
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+ | 0.0209 | 43.0 | 1118 | 0.0319 | 0.9659 | 0.9834 | 0.9746 | 0.9928 |
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+ | 0.0209 | 44.0 | 1144 | 0.0269 | 0.9848 | 0.9759 | 0.9803 | 0.9950 |
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+ | 0.0209 | 45.0 | 1170 | 0.0259 | 0.9804 | 0.9804 | 0.9804 | 0.9950 |
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+ | 0.0209 | 46.0 | 1196 | 0.0306 | 0.9716 | 0.9819 | 0.9767 | 0.9939 |
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+ | 0.0209 | 47.0 | 1222 | 0.0354 | 0.9658 | 0.9789 | 0.9723 | 0.9918 |
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+ | 0.0209 | 48.0 | 1248 | 0.0280 | 0.9746 | 0.9819 | 0.9782 | 0.9937 |
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+ | 0.0209 | 49.0 | 1274 | 0.0266 | 0.9833 | 0.9774 | 0.9803 | 0.9955 |
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+ | 0.0209 | 50.0 | 1300 | 0.0287 | 0.9760 | 0.9819 | 0.9789 | 0.9945 |
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+ | 0.0209 | 51.0 | 1326 | 0.0280 | 0.9818 | 0.9759 | 0.9788 | 0.9950 |
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+ | 0.0209 | 52.0 | 1352 | 0.0316 | 0.9787 | 0.9713 | 0.9750 | 0.9937 |
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+ | 0.0209 | 53.0 | 1378 | 0.0302 | 0.9744 | 0.9774 | 0.9759 | 0.9936 |
111
+ | 0.0209 | 54.0 | 1404 | 0.0309 | 0.9744 | 0.9759 | 0.9751 | 0.9932 |
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+ | 0.0209 | 55.0 | 1430 | 0.0298 | 0.9818 | 0.9759 | 0.9788 | 0.9947 |
113
+ | 0.0209 | 56.0 | 1456 | 0.0291 | 0.9729 | 0.9744 | 0.9736 | 0.9931 |
114
+ | 0.0209 | 57.0 | 1482 | 0.0287 | 0.9773 | 0.9759 | 0.9766 | 0.9937 |
115
+ | 0.0099 | 58.0 | 1508 | 0.0349 | 0.9687 | 0.9789 | 0.9737 | 0.9921 |
116
+ | 0.0099 | 59.0 | 1534 | 0.0295 | 0.9745 | 0.9789 | 0.9767 | 0.9936 |
117
+ | 0.0099 | 60.0 | 1560 | 0.0306 | 0.9759 | 0.9789 | 0.9774 | 0.9936 |
118
+ | 0.0099 | 61.0 | 1586 | 0.0298 | 0.9775 | 0.9819 | 0.9797 | 0.9944 |
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+ | 0.0099 | 62.0 | 1612 | 0.0296 | 0.9746 | 0.9819 | 0.9782 | 0.9944 |
120
+ | 0.0099 | 63.0 | 1638 | 0.0282 | 0.9760 | 0.9804 | 0.9782 | 0.9944 |
121
+ | 0.0099 | 64.0 | 1664 | 0.0290 | 0.9804 | 0.9804 | 0.9804 | 0.9949 |
122
+ | 0.0099 | 65.0 | 1690 | 0.0290 | 0.9745 | 0.9789 | 0.9767 | 0.9937 |
123
+ | 0.0099 | 66.0 | 1716 | 0.0277 | 0.9774 | 0.9789 | 0.9781 | 0.9944 |
124
+ | 0.0099 | 67.0 | 1742 | 0.0303 | 0.9745 | 0.9804 | 0.9774 | 0.9942 |
125
+ | 0.0099 | 68.0 | 1768 | 0.0283 | 0.9773 | 0.9759 | 0.9766 | 0.9945 |
126
+ | 0.0099 | 69.0 | 1794 | 0.0301 | 0.9759 | 0.9774 | 0.9766 | 0.9940 |
127
+ | 0.0099 | 70.0 | 1820 | 0.0304 | 0.9745 | 0.9789 | 0.9767 | 0.9940 |
128
+ | 0.0099 | 71.0 | 1846 | 0.0290 | 0.9789 | 0.9774 | 0.9781 | 0.9944 |
129
+ | 0.0099 | 72.0 | 1872 | 0.0346 | 0.9658 | 0.9789 | 0.9723 | 0.9926 |
130
+ | 0.0099 | 73.0 | 1898 | 0.0327 | 0.9687 | 0.9789 | 0.9737 | 0.9932 |
131
+ | 0.0099 | 74.0 | 1924 | 0.0315 | 0.9759 | 0.9789 | 0.9774 | 0.9940 |
132
+ | 0.0099 | 75.0 | 1950 | 0.0305 | 0.9774 | 0.9774 | 0.9774 | 0.9940 |
133
+ | 0.0099 | 76.0 | 1976 | 0.0304 | 0.9759 | 0.9789 | 0.9774 | 0.9942 |
134
+ | 0.0059 | 77.0 | 2002 | 0.0306 | 0.9716 | 0.9789 | 0.9752 | 0.9936 |
135
+ | 0.0059 | 78.0 | 2028 | 0.0304 | 0.9789 | 0.9789 | 0.9789 | 0.9944 |
136
+ | 0.0059 | 79.0 | 2054 | 0.0322 | 0.9687 | 0.9789 | 0.9737 | 0.9932 |
137
+ | 0.0059 | 80.0 | 2080 | 0.0323 | 0.9730 | 0.9789 | 0.9759 | 0.9936 |
138
+ | 0.0059 | 81.0 | 2106 | 0.0314 | 0.9730 | 0.9789 | 0.9759 | 0.9937 |
139
+ | 0.0059 | 82.0 | 2132 | 0.0315 | 0.9730 | 0.9789 | 0.9759 | 0.9937 |
140
+ | 0.0059 | 83.0 | 2158 | 0.0310 | 0.9731 | 0.9804 | 0.9767 | 0.9939 |
141
+ | 0.0059 | 84.0 | 2184 | 0.0318 | 0.9701 | 0.9804 | 0.9752 | 0.9936 |
142
+ | 0.0059 | 85.0 | 2210 | 0.0317 | 0.9745 | 0.9789 | 0.9767 | 0.9939 |
143
+ | 0.0059 | 86.0 | 2236 | 0.0316 | 0.9745 | 0.9789 | 0.9767 | 0.9939 |
144
+ | 0.0059 | 87.0 | 2262 | 0.0318 | 0.9745 | 0.9789 | 0.9767 | 0.9939 |
145
+ | 0.0059 | 88.0 | 2288 | 0.0324 | 0.9730 | 0.9789 | 0.9759 | 0.9937 |
146
+ | 0.0059 | 89.0 | 2314 | 0.0320 | 0.9745 | 0.9789 | 0.9767 | 0.9939 |
147
+ | 0.0059 | 90.0 | 2340 | 0.0336 | 0.9701 | 0.9789 | 0.9745 | 0.9934 |
148
+ | 0.0059 | 91.0 | 2366 | 0.0335 | 0.9730 | 0.9789 | 0.9759 | 0.9937 |
149
+ | 0.0059 | 92.0 | 2392 | 0.0332 | 0.9745 | 0.9789 | 0.9767 | 0.9939 |
150
+ | 0.0059 | 93.0 | 2418 | 0.0334 | 0.9730 | 0.9789 | 0.9759 | 0.9937 |
151
+ | 0.0059 | 94.0 | 2444 | 0.0335 | 0.9716 | 0.9789 | 0.9752 | 0.9936 |
152
+ | 0.0059 | 95.0 | 2470 | 0.0342 | 0.9701 | 0.9789 | 0.9745 | 0.9931 |
153
+ | 0.0059 | 96.0 | 2496 | 0.0338 | 0.9716 | 0.9789 | 0.9752 | 0.9936 |
154
+ | 0.0045 | 97.0 | 2522 | 0.0338 | 0.9730 | 0.9789 | 0.9759 | 0.9937 |
155
+ | 0.0045 | 98.0 | 2548 | 0.0338 | 0.9716 | 0.9789 | 0.9752 | 0.9936 |
156
+ | 0.0045 | 99.0 | 2574 | 0.0336 | 0.9730 | 0.9789 | 0.9759 | 0.9937 |
157
+ | 0.0045 | 100.0 | 2600 | 0.0336 | 0.9730 | 0.9789 | 0.9759 | 0.9937 |
158
 
159
 
160
  ### Framework versions
model.safetensors CHANGED
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  size 470051652
 
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