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robbert-v2-dutch-base-finetuned-emotion-valence

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  1. README.md +52 -52
  2. model.safetensors +1 -1
  3. runs/Jul29_10-46-29_dc2f8f3965f4/events.out.tfevents.1722249996.dc2f8f3965f4.1637.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -15,8 +15,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [pdelobelle/robbert-v2-dutch-base](https://huggingface.co/pdelobelle/robbert-v2-dutch-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0327
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- - Rmse: 0.1808
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  ## Model description
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@@ -47,56 +47,56 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Rmse |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 0.0887 | 1.0 | 25 | 0.0611 | 0.2472 |
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- | 0.044 | 2.0 | 50 | 0.0403 | 0.2008 |
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- | 0.0356 | 3.0 | 75 | 0.0435 | 0.2085 |
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- | 0.0301 | 4.0 | 100 | 0.0415 | 0.2038 |
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- | 0.0246 | 5.0 | 125 | 0.0377 | 0.1941 |
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- | 0.0224 | 6.0 | 150 | 0.0355 | 0.1885 |
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- | 0.0218 | 7.0 | 175 | 0.0379 | 0.1946 |
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- | 0.0174 | 8.0 | 200 | 0.0436 | 0.2088 |
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- | 0.0156 | 9.0 | 225 | 0.0361 | 0.1901 |
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- | 0.0138 | 10.0 | 250 | 0.0379 | 0.1947 |
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- | 0.0135 | 11.0 | 275 | 0.0386 | 0.1965 |
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- | 0.013 | 12.0 | 300 | 0.0402 | 0.2005 |
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- | 0.0125 | 13.0 | 325 | 0.0325 | 0.1804 |
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- | 0.0117 | 14.0 | 350 | 0.0349 | 0.1868 |
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- | 0.0109 | 15.0 | 375 | 0.0366 | 0.1914 |
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- | 0.0108 | 16.0 | 400 | 0.0382 | 0.1953 |
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- | 0.0091 | 17.0 | 425 | 0.0336 | 0.1833 |
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- | 0.0097 | 18.0 | 450 | 0.0325 | 0.1802 |
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- | 0.0098 | 19.0 | 475 | 0.0406 | 0.2014 |
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- | 0.0094 | 20.0 | 500 | 0.0330 | 0.1816 |
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- | 0.0088 | 21.0 | 525 | 0.0349 | 0.1868 |
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- | 0.0087 | 22.0 | 550 | 0.0337 | 0.1835 |
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- | 0.0079 | 23.0 | 575 | 0.0340 | 0.1845 |
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- | 0.0074 | 24.0 | 600 | 0.0372 | 0.1928 |
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- | 0.007 | 25.0 | 625 | 0.0345 | 0.1856 |
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- | 0.0072 | 26.0 | 650 | 0.0333 | 0.1824 |
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- | 0.0074 | 27.0 | 675 | 0.0308 | 0.1756 |
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- | 0.0071 | 28.0 | 700 | 0.0314 | 0.1772 |
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- | 0.0067 | 29.0 | 725 | 0.0314 | 0.1772 |
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- | 0.0065 | 30.0 | 750 | 0.0333 | 0.1824 |
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- | 0.0072 | 31.0 | 775 | 0.0337 | 0.1837 |
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- | 0.0065 | 32.0 | 800 | 0.0351 | 0.1873 |
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- | 0.0057 | 33.0 | 825 | 0.0330 | 0.1818 |
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- | 0.0067 | 34.0 | 850 | 0.0367 | 0.1915 |
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- | 0.0061 | 35.0 | 875 | 0.0358 | 0.1893 |
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- | 0.0062 | 36.0 | 900 | 0.0353 | 0.1879 |
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- | 0.006 | 37.0 | 925 | 0.0317 | 0.1779 |
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- | 0.0059 | 38.0 | 950 | 0.0331 | 0.1819 |
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- | 0.0058 | 39.0 | 975 | 0.0308 | 0.1755 |
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- | 0.0057 | 40.0 | 1000 | 0.0338 | 0.1838 |
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- | 0.0055 | 41.0 | 1025 | 0.0324 | 0.1800 |
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- | 0.0056 | 42.0 | 1050 | 0.0333 | 0.1824 |
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- | 0.0054 | 43.0 | 1075 | 0.0331 | 0.1819 |
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- | 0.0062 | 44.0 | 1100 | 0.0329 | 0.1813 |
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- | 0.0056 | 45.0 | 1125 | 0.0325 | 0.1802 |
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- | 0.0051 | 46.0 | 1150 | 0.0324 | 0.1801 |
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- | 0.0056 | 47.0 | 1175 | 0.0322 | 0.1795 |
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- | 0.0056 | 48.0 | 1200 | 0.0331 | 0.1818 |
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- | 0.0053 | 49.0 | 1225 | 0.0322 | 0.1794 |
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- | 0.0056 | 50.0 | 1250 | 0.0327 | 0.1808 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [pdelobelle/robbert-v2-dutch-base](https://huggingface.co/pdelobelle/robbert-v2-dutch-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0317
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+ - Rmse: 0.1781
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Rmse |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 0.0813 | 1.0 | 25 | 0.0510 | 0.2258 |
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+ | 0.0445 | 2.0 | 50 | 0.0381 | 0.1952 |
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+ | 0.0409 | 3.0 | 75 | 0.0466 | 0.2158 |
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+ | 0.0308 | 4.0 | 100 | 0.0351 | 0.1874 |
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+ | 0.0257 | 5.0 | 125 | 0.0393 | 0.1983 |
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+ | 0.0231 | 6.0 | 150 | 0.0442 | 0.2103 |
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+ | 0.0203 | 7.0 | 175 | 0.0447 | 0.2115 |
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+ | 0.0191 | 8.0 | 200 | 0.0372 | 0.1929 |
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+ | 0.0156 | 9.0 | 225 | 0.0425 | 0.2061 |
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+ | 0.0154 | 10.0 | 250 | 0.0367 | 0.1917 |
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+ | 0.0138 | 11.0 | 275 | 0.0365 | 0.1910 |
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+ | 0.0128 | 12.0 | 300 | 0.0432 | 0.2078 |
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+ | 0.0137 | 13.0 | 325 | 0.0329 | 0.1814 |
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+ | 0.0118 | 14.0 | 350 | 0.0327 | 0.1809 |
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+ | 0.0118 | 15.0 | 375 | 0.0378 | 0.1945 |
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+ | 0.0109 | 16.0 | 400 | 0.0360 | 0.1897 |
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+ | 0.0103 | 17.0 | 425 | 0.0325 | 0.1803 |
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+ | 0.0096 | 18.0 | 450 | 0.0327 | 0.1809 |
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+ | 0.0091 | 19.0 | 475 | 0.0430 | 0.2072 |
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+ | 0.0081 | 20.0 | 500 | 0.0345 | 0.1856 |
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+ | 0.0094 | 21.0 | 525 | 0.0365 | 0.1912 |
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+ | 0.0084 | 22.0 | 550 | 0.0350 | 0.1870 |
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+ | 0.0075 | 23.0 | 575 | 0.0324 | 0.1800 |
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+ | 0.0069 | 24.0 | 600 | 0.0330 | 0.1816 |
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+ | 0.0087 | 25.0 | 625 | 0.0347 | 0.1863 |
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+ | 0.0079 | 26.0 | 650 | 0.0297 | 0.1722 |
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+ | 0.0071 | 27.0 | 675 | 0.0311 | 0.1763 |
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+ | 0.0076 | 28.0 | 700 | 0.0322 | 0.1795 |
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+ | 0.0064 | 29.0 | 725 | 0.0338 | 0.1839 |
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+ | 0.0067 | 30.0 | 750 | 0.0326 | 0.1806 |
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+ | 0.0061 | 31.0 | 775 | 0.0327 | 0.1808 |
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+ | 0.0064 | 32.0 | 800 | 0.0339 | 0.1842 |
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+ | 0.0062 | 33.0 | 825 | 0.0300 | 0.1732 |
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+ | 0.0062 | 34.0 | 850 | 0.0331 | 0.1819 |
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+ | 0.0055 | 35.0 | 875 | 0.0318 | 0.1782 |
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+ | 0.0059 | 36.0 | 900 | 0.0323 | 0.1797 |
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+ | 0.0056 | 37.0 | 925 | 0.0311 | 0.1765 |
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+ | 0.0055 | 38.0 | 950 | 0.0310 | 0.1762 |
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+ | 0.0053 | 39.0 | 975 | 0.0325 | 0.1802 |
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+ | 0.0056 | 40.0 | 1000 | 0.0310 | 0.1761 |
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+ | 0.0054 | 41.0 | 1025 | 0.0323 | 0.1799 |
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+ | 0.0057 | 42.0 | 1050 | 0.0351 | 0.1873 |
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+ | 0.0053 | 43.0 | 1075 | 0.0347 | 0.1861 |
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+ | 0.0054 | 44.0 | 1100 | 0.0330 | 0.1816 |
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+ | 0.0059 | 45.0 | 1125 | 0.0313 | 0.1769 |
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+ | 0.0053 | 46.0 | 1150 | 0.0312 | 0.1766 |
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+ | 0.0051 | 47.0 | 1175 | 0.0325 | 0.1804 |
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+ | 0.0057 | 48.0 | 1200 | 0.0304 | 0.1745 |
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+ | 0.0048 | 49.0 | 1225 | 0.0317 | 0.1782 |
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+ | 0.005 | 50.0 | 1250 | 0.0317 | 0.1781 |
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  ### Framework versions
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