End of training
Browse files
README.md
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@@ -20,12 +20,12 @@ should probably proofread and complete it, then remove this comment. -->
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This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy: 0.
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- Precision: 0.
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- Recall: 0.
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- F1: 0.
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- Binary: 0.
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## Model description
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@@ -59,153 +59,101 @@ The following hyperparameters were used during training:
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Binary |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
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| No log | 0.13 | 50 | 3.
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| No log | 0.27 | 100 | 3.
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| No log | 0.4 | 150 |
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| No log | 0.54 | 200 |
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| No log | 0.67 | 250 | 2.
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| No log | 0.81 | 300 |
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| No log | 0.94 | 350 |
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| 0.2736 | 12.94 | 4800 | 0.7166 | 0.8718 | 0.8864 | 0.8718 | 0.8695 | 0.9105 |
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| 0.2541 | 13.07 | 4850 | 0.5717 | 0.8866 | 0.9001 | 0.8866 | 0.8858 | 0.9198 |
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| 0.2541 | 13.21 | 4900 | 0.6211 | 0.8745 | 0.8910 | 0.8745 | 0.8735 | 0.9123 |
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| 0.2541 | 13.34 | 4950 | 0.5923 | 0.8799 | 0.8975 | 0.8799 | 0.8805 | 0.9151 |
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| 0.2541 | 13.48 | 5000 | 0.5885 | 0.8758 | 0.8891 | 0.8758 | 0.8759 | 0.9132 |
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| 0.2541 | 13.61 | 5050 | 0.6245 | 0.8866 | 0.8998 | 0.8866 | 0.8862 | 0.9192 |
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| 0.2541 | 13.75 | 5100 | 0.6897 | 0.8718 | 0.8866 | 0.8718 | 0.8706 | 0.9090 |
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| 0.2541 | 13.88 | 5150 | 0.6919 | 0.8677 | 0.8807 | 0.8677 | 0.8677 | 0.9076 |
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| 0.2384 | 14.02 | 5200 | 0.5996 | 0.8961 | 0.9079 | 0.8961 | 0.8951 | 0.9269 |
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| 0.2384 | 14.15 | 5250 | 0.6649 | 0.8880 | 0.9013 | 0.8880 | 0.8861 | 0.9208 |
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| 0.2384 | 14.29 | 5300 | 0.7136 | 0.8664 | 0.8854 | 0.8664 | 0.8625 | 0.9061 |
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| 0.2384 | 14.42 | 5350 | 0.6670 | 0.8812 | 0.8970 | 0.8812 | 0.8812 | 0.9158 |
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| 0.2384 | 14.56 | 5400 | 0.6286 | 0.8826 | 0.8952 | 0.8826 | 0.8820 | 0.9175 |
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| 0.2384 | 14.69 | 5450 | 0.6297 | 0.8785 | 0.8877 | 0.8785 | 0.8755 | 0.9151 |
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| 0.2384 | 14.82 | 5500 | 0.7010 | 0.8799 | 0.8953 | 0.8799 | 0.8795 | 0.9159 |
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| 0.2384 | 14.96 | 5550 | 0.6078 | 0.8853 | 0.8985 | 0.8853 | 0.8822 | 0.9197 |
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| 0.2218 | 15.09 | 5600 | 0.6684 | 0.8758 | 0.8917 | 0.8758 | 0.8751 | 0.9127 |
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| 0.2218 | 15.23 | 5650 | 0.6672 | 0.8799 | 0.8917 | 0.8799 | 0.8774 | 0.9157 |
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| 0.2218 | 15.36 | 5700 | 0.6440 | 0.8839 | 0.8998 | 0.8839 | 0.8828 | 0.9189 |
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| 0.2218 | 15.5 | 5750 | 0.6807 | 0.8866 | 0.9002 | 0.8866 | 0.8863 | 0.9204 |
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| 0.2218 | 15.63 | 5800 | 0.6325 | 0.8839 | 0.8949 | 0.8839 | 0.8831 | 0.9184 |
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| 0.2218 | 15.77 | 5850 | 0.6078 | 0.8934 | 0.9046 | 0.8934 | 0.8918 | 0.9250 |
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| 0.2218 | 15.9 | 5900 | 0.6638 | 0.8866 | 0.9005 | 0.8866 | 0.8860 | 0.9202 |
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| 0.2192 | 16.04 | 5950 | 0.5822 | 0.8920 | 0.9044 | 0.8920 | 0.8910 | 0.9240 |
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| 0.2192 | 16.17 | 6000 | 0.6028 | 0.8785 | 0.8922 | 0.8785 | 0.8765 | 0.9138 |
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| 0.2192 | 16.31 | 6050 | 0.6012 | 0.8893 | 0.9013 | 0.8893 | 0.8884 | 0.9227 |
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| 0.2192 | 16.44 | 6100 | 0.5819 | 0.8853 | 0.8980 | 0.8853 | 0.8838 | 0.9193 |
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| 0.2192 | 16.58 | 6150 | 0.6055 | 0.8826 | 0.8998 | 0.8826 | 0.8818 | 0.9170 |
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| 0.2192 | 16.71 | 6200 | 0.6642 | 0.9001 | 0.9123 | 0.9001 | 0.8991 | 0.9297 |
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| 0.2192 | 16.85 | 6250 | 0.6235 | 0.8880 | 0.8976 | 0.8880 | 0.8857 | 0.9219 |
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| 0.2192 | 16.98 | 6300 | 0.5460 | 0.8920 | 0.9007 | 0.8920 | 0.8905 | 0.9240 |
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| 0.2103 | 17.12 | 6350 | 0.5525 | 0.8920 | 0.9031 | 0.8920 | 0.8908 | 0.9242 |
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| 0.2103 | 17.25 | 6400 | 0.5847 | 0.8974 | 0.9092 | 0.8974 | 0.8960 | 0.9279 |
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| 0.2103 | 17.39 | 6450 | 0.5585 | 0.8961 | 0.9081 | 0.8961 | 0.8958 | 0.9260 |
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| 0.2103 | 17.52 | 6500 | 0.5424 | 0.8920 | 0.9008 | 0.8920 | 0.8911 | 0.9247 |
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| 0.2103 | 17.65 | 6550 | 0.5473 | 0.9042 | 0.9141 | 0.9042 | 0.9032 | 0.9331 |
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| 0.2103 | 17.79 | 6600 | 0.5548 | 0.9001 | 0.9081 | 0.9001 | 0.8990 | 0.9308 |
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| 0.2103 | 17.92 | 6650 | 0.6355 | 0.8866 | 0.8983 | 0.8866 | 0.8839 | 0.9194 |
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| 0.1962 | 18.06 | 6700 | 0.5878 | 0.9015 | 0.9120 | 0.9015 | 0.8983 | 0.9306 |
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| 0.1962 | 18.19 | 6750 | 0.6067 | 0.8907 | 0.9015 | 0.8907 | 0.8890 | 0.9231 |
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| 0.1962 | 18.33 | 6800 | 0.5797 | 0.8880 | 0.8989 | 0.8880 | 0.8863 | 0.9212 |
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| 0.1962 | 18.46 | 6850 | 0.5842 | 0.8907 | 0.9020 | 0.8907 | 0.8894 | 0.9236 |
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| 0.1962 | 18.6 | 6900 | 0.5838 | 0.8961 | 0.9078 | 0.8961 | 0.8947 | 0.9260 |
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| 0.1962 | 18.73 | 6950 | 0.5655 | 0.8880 | 0.9021 | 0.8880 | 0.8876 | 0.9212 |
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| 0.1962 | 18.87 | 7000 | 0.5601 | 0.8988 | 0.9088 | 0.8988 | 0.8977 | 0.9287 |
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| 0.1881 | 19.0 | 7050 | 0.5815 | 0.8988 | 0.9077 | 0.8988 | 0.8972 | 0.9283 |
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| 0.1881 | 19.14 | 7100 | 0.6380 | 0.8947 | 0.9054 | 0.8947 | 0.8932 | 0.9259 |
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| 0.1881 | 19.27 | 7150 | 0.6770 | 0.8907 | 0.9004 | 0.8907 | 0.8892 | 0.9227 |
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| 0.1881 | 19.41 | 7200 | 0.6608 | 0.8907 | 0.8997 | 0.8907 | 0.8890 | 0.9227 |
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| 0.1881 | 19.54 | 7250 | 0.7075 | 0.8826 | 0.8974 | 0.8826 | 0.8815 | 0.9174 |
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| 0.1881 | 19.68 | 7300 | 0.6649 | 0.8853 | 0.8992 | 0.8853 | 0.8827 | 0.9193 |
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| 0.1881 | 19.81 | 7350 | 0.6430 | 0.8880 | 0.8983 | 0.8880 | 0.8868 | 0.9212 |
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### Framework versions
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This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7308
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- Accuracy: 0.8585
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- Precision: 0.8738
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- Recall: 0.8585
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- F1: 0.8578
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- Binary: 0.8997
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Binary |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
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| No log | 0.13 | 50 | 3.8576 | 0.0621 | 0.0074 | 0.0621 | 0.0112 | 0.3362 |
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| No log | 0.27 | 100 | 3.4091 | 0.0931 | 0.0349 | 0.0931 | 0.0334 | 0.3617 |
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| No log | 0.4 | 150 | 3.2224 | 0.1053 | 0.0231 | 0.1053 | 0.0330 | 0.3698 |
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| No log | 0.54 | 200 | 3.0715 | 0.1215 | 0.0509 | 0.1215 | 0.0558 | 0.3800 |
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| No log | 0.67 | 250 | 2.7013 | 0.2416 | 0.1533 | 0.2416 | 0.1549 | 0.4665 |
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| No log | 0.81 | 300 | 2.4186 | 0.3077 | 0.2216 | 0.3077 | 0.2178 | 0.5124 |
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| No log | 0.94 | 350 | 2.2086 | 0.3725 | 0.2827 | 0.3725 | 0.2882 | 0.5592 |
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| 3.209 | 1.08 | 400 | 1.9624 | 0.4534 | 0.4314 | 0.4534 | 0.3907 | 0.6155 |
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| 3.209 | 1.21 | 450 | 1.7552 | 0.5344 | 0.4957 | 0.5344 | 0.4788 | 0.6735 |
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| 3.209 | 1.35 | 500 | 1.5887 | 0.5668 | 0.5359 | 0.5668 | 0.5127 | 0.6957 |
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| 3.209 | 1.48 | 550 | 1.4249 | 0.6073 | 0.5999 | 0.6073 | 0.5671 | 0.7248 |
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| 3.209 | 1.62 | 600 | 1.2562 | 0.6397 | 0.6424 | 0.6397 | 0.6007 | 0.7486 |
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| 3.209 | 1.75 | 650 | 1.1504 | 0.6680 | 0.6724 | 0.6680 | 0.6379 | 0.7683 |
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| 3.209 | 1.89 | 700 | 1.0797 | 0.6991 | 0.7111 | 0.6991 | 0.6753 | 0.7896 |
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| 1.7186 | 2.02 | 750 | 1.0473 | 0.7314 | 0.7634 | 0.7314 | 0.7173 | 0.8139 |
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| 1.7186 | 2.16 | 800 | 0.9383 | 0.7503 | 0.7777 | 0.7503 | 0.7343 | 0.8271 |
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| 1.7186 | 2.29 | 850 | 0.9288 | 0.7679 | 0.7842 | 0.7679 | 0.7567 | 0.8393 |
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| 1.7186 | 2.43 | 900 | 0.8284 | 0.7746 | 0.7897 | 0.7746 | 0.7679 | 0.8432 |
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| 1.7186 | 2.56 | 950 | 0.8246 | 0.7800 | 0.8108 | 0.7800 | 0.7729 | 0.8474 |
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| 1.7186 | 2.7 | 1000 | 0.8581 | 0.7665 | 0.7893 | 0.7665 | 0.7586 | 0.8370 |
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| 1.7186 | 2.83 | 1050 | 0.7753 | 0.7962 | 0.8151 | 0.7962 | 0.7919 | 0.8583 |
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| 1.7186 | 2.96 | 1100 | 0.7556 | 0.8043 | 0.8205 | 0.8043 | 0.7965 | 0.8641 |
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| 1.0562 | 3.1 | 1150 | 0.8130 | 0.7962 | 0.8149 | 0.7962 | 0.7913 | 0.8567 |
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| 1.0562 | 3.23 | 1200 | 0.7633 | 0.7895 | 0.8189 | 0.7895 | 0.7880 | 0.8528 |
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| 1.0562 | 3.37 | 1250 | 0.6852 | 0.8178 | 0.8352 | 0.8178 | 0.8135 | 0.8742 |
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| 1.0562 | 3.5 | 1300 | 0.8465 | 0.7638 | 0.8001 | 0.7638 | 0.7588 | 0.8347 |
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| 1.0562 | 3.64 | 1350 | 0.7130 | 0.8111 | 0.8215 | 0.8111 | 0.8026 | 0.8686 |
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| 1.0562 | 3.77 | 1400 | 0.7425 | 0.8057 | 0.8242 | 0.8057 | 0.8040 | 0.8657 |
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| 1.0562 | 3.91 | 1450 | 0.7719 | 0.8057 | 0.8220 | 0.8057 | 0.8030 | 0.8634 |
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| 0.782 | 4.04 | 1500 | 0.6581 | 0.8354 | 0.8497 | 0.8354 | 0.8332 | 0.8850 |
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| 0.782 | 4.18 | 1550 | 0.7134 | 0.8124 | 0.8281 | 0.8124 | 0.8095 | 0.8682 |
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| 0.782 | 4.31 | 1600 | 0.6923 | 0.8259 | 0.8455 | 0.8259 | 0.8234 | 0.8795 |
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| 0.782 | 4.45 | 1650 | 0.6699 | 0.8367 | 0.8539 | 0.8367 | 0.8347 | 0.8868 |
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| 0.782 | 4.58 | 1700 | 0.6169 | 0.8475 | 0.8597 | 0.8475 | 0.8456 | 0.8926 |
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| 0.782 | 4.72 | 1750 | 0.6198 | 0.8381 | 0.8491 | 0.8381 | 0.8349 | 0.8870 |
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| 0.782 | 4.85 | 1800 | 0.6939 | 0.8313 | 0.8502 | 0.8313 | 0.8318 | 0.8823 |
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| 0.782 | 4.99 | 1850 | 0.7710 | 0.8205 | 0.8408 | 0.8205 | 0.8147 | 0.8729 |
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| 0.6114 | 5.12 | 1900 | 0.6556 | 0.8381 | 0.8495 | 0.8381 | 0.8362 | 0.8880 |
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| 0.6114 | 5.26 | 1950 | 0.7667 | 0.8151 | 0.8332 | 0.8151 | 0.8129 | 0.8698 |
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| 0.6114 | 5.39 | 2000 | 0.7299 | 0.8232 | 0.8413 | 0.8232 | 0.8200 | 0.8748 |
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| 0.6114 | 5.53 | 2050 | 0.7309 | 0.8327 | 0.8419 | 0.8327 | 0.8266 | 0.8835 |
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| 0.6114 | 5.66 | 2100 | 0.7464 | 0.8192 | 0.8344 | 0.8192 | 0.8165 | 0.8750 |
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| 0.6114 | 5.8 | 2150 | 0.7440 | 0.8340 | 0.8484 | 0.8340 | 0.8323 | 0.8849 |
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| 0.6114 | 5.93 | 2200 | 0.7002 | 0.8475 | 0.8594 | 0.8475 | 0.8455 | 0.8935 |
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| 0.5068 | 6.06 | 2250 | 0.7030 | 0.8448 | 0.8599 | 0.8448 | 0.8421 | 0.8912 |
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| 0.5068 | 6.2 | 2300 | 0.7355 | 0.8421 | 0.8560 | 0.8421 | 0.8398 | 0.8889 |
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| 0.5068 | 6.33 | 2350 | 0.7511 | 0.8246 | 0.8339 | 0.8246 | 0.8209 | 0.8771 |
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| 0.5068 | 6.47 | 2400 | 0.6739 | 0.8421 | 0.8534 | 0.8421 | 0.8408 | 0.8903 |
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| 0.5068 | 6.6 | 2450 | 0.6982 | 0.8475 | 0.8654 | 0.8475 | 0.8441 | 0.8931 |
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| 0.5068 | 6.74 | 2500 | 0.7522 | 0.8408 | 0.8531 | 0.8408 | 0.8394 | 0.8880 |
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| 0.5068 | 6.87 | 2550 | 0.7261 | 0.8354 | 0.8479 | 0.8354 | 0.8323 | 0.8856 |
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| 0.4429 | 7.01 | 2600 | 0.7445 | 0.8421 | 0.8557 | 0.8421 | 0.8402 | 0.8896 |
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| 0.4429 | 7.14 | 2650 | 0.7698 | 0.8327 | 0.8406 | 0.8327 | 0.8290 | 0.8823 |
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| 0.4429 | 7.28 | 2700 | 0.8428 | 0.8273 | 0.8433 | 0.8273 | 0.8254 | 0.8806 |
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| 0.4429 | 7.41 | 2750 | 0.8403 | 0.8259 | 0.8443 | 0.8259 | 0.8242 | 0.8789 |
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| 0.4429 | 7.55 | 2800 | 0.7045 | 0.8381 | 0.8527 | 0.8381 | 0.8372 | 0.8866 |
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| 0.4429 | 7.68 | 2850 | 0.8546 | 0.8327 | 0.8441 | 0.8327 | 0.8309 | 0.8825 |
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| 0.4429 | 7.82 | 2900 | 0.7722 | 0.8340 | 0.8511 | 0.8340 | 0.8350 | 0.8830 |
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120 |
+
| 0.4429 | 7.95 | 2950 | 0.7198 | 0.8435 | 0.8590 | 0.8435 | 0.8432 | 0.8927 |
|
121 |
+
| 0.3872 | 8.09 | 3000 | 0.7239 | 0.8408 | 0.8510 | 0.8408 | 0.8382 | 0.8914 |
|
122 |
+
| 0.3872 | 8.22 | 3050 | 0.7778 | 0.8475 | 0.8572 | 0.8475 | 0.8452 | 0.8950 |
|
123 |
+
| 0.3872 | 8.36 | 3100 | 0.8277 | 0.8394 | 0.8513 | 0.8394 | 0.8378 | 0.8892 |
|
124 |
+
| 0.3872 | 8.49 | 3150 | 0.7813 | 0.8462 | 0.8587 | 0.8462 | 0.8459 | 0.8912 |
|
125 |
+
| 0.3872 | 8.63 | 3200 | 0.7736 | 0.8394 | 0.8503 | 0.8394 | 0.8373 | 0.8880 |
|
126 |
+
| 0.3872 | 8.76 | 3250 | 0.7917 | 0.8394 | 0.8530 | 0.8394 | 0.8371 | 0.8883 |
|
127 |
+
| 0.3872 | 8.89 | 3300 | 0.7909 | 0.8475 | 0.8565 | 0.8475 | 0.8456 | 0.8930 |
|
128 |
+
| 0.3527 | 9.03 | 3350 | 0.7729 | 0.8529 | 0.8659 | 0.8529 | 0.8506 | 0.8977 |
|
129 |
+
| 0.3527 | 9.16 | 3400 | 0.8406 | 0.8475 | 0.8635 | 0.8475 | 0.8443 | 0.8937 |
|
130 |
+
| 0.3527 | 9.3 | 3450 | 0.7908 | 0.8435 | 0.8561 | 0.8435 | 0.8406 | 0.8910 |
|
131 |
+
| 0.3527 | 9.43 | 3500 | 0.8294 | 0.8300 | 0.8432 | 0.8300 | 0.8279 | 0.8808 |
|
132 |
+
| 0.3527 | 9.57 | 3550 | 0.8214 | 0.8421 | 0.8559 | 0.8421 | 0.8418 | 0.8897 |
|
133 |
+
| 0.3527 | 9.7 | 3600 | 0.8200 | 0.8435 | 0.8571 | 0.8435 | 0.8426 | 0.8918 |
|
134 |
+
| 0.3527 | 9.84 | 3650 | 0.7658 | 0.8502 | 0.8594 | 0.8502 | 0.8487 | 0.8969 |
|
135 |
+
| 0.3527 | 9.97 | 3700 | 0.8817 | 0.8354 | 0.8505 | 0.8354 | 0.8350 | 0.8842 |
|
136 |
+
| 0.3278 | 10.11 | 3750 | 0.8310 | 0.8489 | 0.8660 | 0.8489 | 0.8493 | 0.8950 |
|
137 |
+
| 0.3278 | 10.24 | 3800 | 0.6998 | 0.8664 | 0.8765 | 0.8664 | 0.8654 | 0.9072 |
|
138 |
+
| 0.3278 | 10.38 | 3850 | 0.7762 | 0.8435 | 0.8588 | 0.8435 | 0.8439 | 0.8904 |
|
139 |
+
| 0.3278 | 10.51 | 3900 | 0.9134 | 0.8435 | 0.8563 | 0.8435 | 0.8427 | 0.8920 |
|
140 |
+
| 0.3278 | 10.65 | 3950 | 0.7972 | 0.8556 | 0.8722 | 0.8556 | 0.8542 | 0.8988 |
|
141 |
+
| 0.3278 | 10.78 | 4000 | 0.8311 | 0.8610 | 0.8727 | 0.8610 | 0.8598 | 0.9043 |
|
142 |
+
| 0.3278 | 10.92 | 4050 | 0.8660 | 0.8543 | 0.8647 | 0.8543 | 0.8540 | 0.8993 |
|
143 |
+
| 0.2997 | 11.05 | 4100 | 0.8472 | 0.8556 | 0.8679 | 0.8556 | 0.8544 | 0.8988 |
|
144 |
+
| 0.2997 | 11.19 | 4150 | 0.7564 | 0.8556 | 0.8672 | 0.8556 | 0.8544 | 0.9001 |
|
145 |
+
| 0.2997 | 11.32 | 4200 | 0.7832 | 0.8529 | 0.8684 | 0.8529 | 0.8527 | 0.9005 |
|
146 |
+
| 0.2997 | 11.46 | 4250 | 0.8058 | 0.8623 | 0.8735 | 0.8623 | 0.8591 | 0.9049 |
|
147 |
+
| 0.2997 | 11.59 | 4300 | 0.7588 | 0.8623 | 0.8788 | 0.8623 | 0.8613 | 0.9054 |
|
148 |
+
| 0.2997 | 11.73 | 4350 | 0.8209 | 0.8462 | 0.8658 | 0.8462 | 0.8472 | 0.8926 |
|
149 |
+
| 0.2997 | 11.86 | 4400 | 0.7649 | 0.8650 | 0.8815 | 0.8650 | 0.8660 | 0.9043 |
|
150 |
+
| 0.2997 | 11.99 | 4450 | 0.7985 | 0.8529 | 0.8671 | 0.8529 | 0.8514 | 0.8966 |
|
151 |
+
| 0.283 | 12.13 | 4500 | 0.7353 | 0.8543 | 0.8640 | 0.8543 | 0.8529 | 0.8977 |
|
152 |
+
| 0.283 | 12.26 | 4550 | 0.7714 | 0.8543 | 0.8658 | 0.8543 | 0.8529 | 0.8992 |
|
153 |
+
| 0.283 | 12.4 | 4600 | 0.8393 | 0.8502 | 0.8629 | 0.8502 | 0.8476 | 0.8945 |
|
154 |
+
| 0.283 | 12.53 | 4650 | 0.7847 | 0.8556 | 0.8652 | 0.8556 | 0.8534 | 0.9001 |
|
155 |
+
| 0.283 | 12.67 | 4700 | 0.8041 | 0.8623 | 0.8722 | 0.8623 | 0.8590 | 0.9043 |
|
156 |
+
| 0.283 | 12.8 | 4750 | 0.8478 | 0.8475 | 0.8592 | 0.8475 | 0.8458 | 0.8939 |
|
|
|
|
|
|
|
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|
157 |
|
158 |
|
159 |
### Framework versions
|
model.safetensors
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
size 378386248
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:56d98de48d985754df5e4cedc7c3fbafbf1af93f4646de85db78ca9c5e681bf7
|
3 |
size 378386248
|
runs/Jul20_03-47-40_LAPTOP-1GID9RGH/events.out.tfevents.1721422061.LAPTOP-1GID9RGH.19084.4
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:1b337b5abe194f636ebcc1a7d04612cebd7bbdc08e6ccc9f4636e3f73a1888ac
|
3 |
+
size 61746
|
runs/Jul20_03-47-40_LAPTOP-1GID9RGH/events.out.tfevents.1721425806.LAPTOP-1GID9RGH.19084.5
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:41f45b7c7fb9b6fbb6c35897bf6194116b14200324fb38726f63ea625fea5ba2
|
3 |
+
size 610
|