End of training
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README.md
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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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@@ -59,133 +59,123 @@ 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 | 0.19 | 50 | 4.
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| No log | 0.38 | 100 | 3.
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| No log | 0.58 | 150 | 3.
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| No log | 0.77 | 200 | 3.
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| No log | 0.96 | 250 | 3.
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| 0.7057 | 22.63 | 5900 | 0.6288 | 0.8571 | 0.8693 | 0.8571 | 0.8491 | 0.8984 |
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| 0.7057 | 22.82 | 5950 | 0.6246 | 0.8544 | 0.8749 | 0.8544 | 0.8490 | 0.8965 |
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| 181 |
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| 0.695 | 23.01 | 6000 | 0.5991 | 0.8679 | 0.8874 | 0.8679 | 0.8645 | 0.9059 |
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| 182 |
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| 0.695 | 23.2 | 6050 | 0.6234 | 0.8598 | 0.8816 | 0.8598 | 0.8556 | 0.9003 |
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| 183 |
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| 0.695 | 23.39 | 6100 | 0.5764 | 0.8679 | 0.8885 | 0.8679 | 0.8641 | 0.9059 |
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| 184 |
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| 0.695 | 23.59 | 6150 | 0.6290 | 0.8518 | 0.8641 | 0.8518 | 0.8453 | 0.8946 |
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| 185 |
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| 0.695 | 23.78 | 6200 | 0.6267 | 0.8518 | 0.8634 | 0.8518 | 0.8433 | 0.8946 |
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| 186 |
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| 0.695 | 23.97 | 6250 | 0.6294 | 0.8491 | 0.8582 | 0.8491 | 0.8404 | 0.8927 |
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| 0.6782 | 24.16 | 6300 | 0.6001 | 0.8491 | 0.8618 | 0.8491 | 0.8421 | 0.8927 |
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| 0.6782 | 24.35 | 6350 | 0.6042 | 0.8598 | 0.8687 | 0.8598 | 0.8530 | 0.9003 |
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### Framework versions
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|
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|
| 20 |
|
| 21 |
This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on an unknown dataset.
|
| 22 |
It achieves the following results on the evaluation set:
|
| 23 |
+
- Loss: 0.5721
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| 24 |
+
- Accuracy: 0.8706
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| 25 |
+
- Precision: 0.8813
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| 26 |
+
- Recall: 0.8706
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| 27 |
+
- F1: 0.8644
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| 28 |
+
- Binary: 0.9094
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| 29 |
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| 30 |
## Model description
|
| 31 |
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| 59 |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Binary |
|
| 61 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
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| 62 |
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| No log | 0.19 | 50 | 4.4259 | 0.0135 | 0.0002 | 0.0135 | 0.0004 | 0.1278 |
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| 63 |
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| No log | 0.38 | 100 | 3.8225 | 0.0485 | 0.0033 | 0.0485 | 0.0060 | 0.3151 |
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| 64 |
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| No log | 0.58 | 150 | 3.3928 | 0.0701 | 0.0104 | 0.0701 | 0.0169 | 0.3450 |
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| 65 |
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| No log | 0.77 | 200 | 3.2088 | 0.0836 | 0.0166 | 0.0836 | 0.0258 | 0.3553 |
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| 66 |
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| No log | 0.96 | 250 | 3.0752 | 0.1078 | 0.0279 | 0.1078 | 0.0388 | 0.3714 |
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| 67 |
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| 3.8204 | 1.15 | 300 | 2.9617 | 0.1186 | 0.0338 | 0.1186 | 0.0443 | 0.3776 |
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| 68 |
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| 3.8204 | 1.34 | 350 | 2.7928 | 0.1617 | 0.0704 | 0.1617 | 0.0848 | 0.4100 |
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| 3.8204 | 1.53 | 400 | 2.5904 | 0.2237 | 0.1640 | 0.2237 | 0.1427 | 0.4542 |
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| 3.8204 | 1.73 | 450 | 2.3895 | 0.2615 | 0.1634 | 0.2615 | 0.1771 | 0.4814 |
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| 3.8204 | 1.92 | 500 | 2.2567 | 0.2992 | 0.2170 | 0.2992 | 0.2160 | 0.5097 |
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| 2.9288 | 2.11 | 550 | 2.0903 | 0.3801 | 0.2993 | 0.3801 | 0.3008 | 0.5668 |
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| 2.9288 | 2.3 | 600 | 1.9624 | 0.4151 | 0.3638 | 0.4151 | 0.3389 | 0.5900 |
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| 2.9288 | 2.49 | 650 | 1.7353 | 0.5148 | 0.4641 | 0.5148 | 0.4447 | 0.6625 |
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| 2.9288 | 2.68 | 700 | 1.6687 | 0.5013 | 0.4658 | 0.5013 | 0.4433 | 0.6526 |
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| 76 |
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| 2.9288 | 2.88 | 750 | 1.5726 | 0.5391 | 0.5299 | 0.5391 | 0.4914 | 0.6817 |
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| 2.2908 | 3.07 | 800 | 1.4471 | 0.5714 | 0.5785 | 0.5714 | 0.5269 | 0.7003 |
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| 78 |
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| 2.2908 | 3.26 | 850 | 1.3350 | 0.6334 | 0.6432 | 0.6334 | 0.6040 | 0.7445 |
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| 79 |
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| 2.2908 | 3.45 | 900 | 1.1787 | 0.6685 | 0.6811 | 0.6685 | 0.6349 | 0.7690 |
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| 80 |
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| 2.2908 | 3.64 | 950 | 1.1315 | 0.6846 | 0.6962 | 0.6846 | 0.6524 | 0.7803 |
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| 81 |
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| 2.2908 | 3.84 | 1000 | 1.0283 | 0.7493 | 0.7751 | 0.7493 | 0.7298 | 0.8248 |
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| 82 |
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| 1.8601 | 4.03 | 1050 | 1.0553 | 0.7089 | 0.7311 | 0.7089 | 0.6824 | 0.7984 |
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| 83 |
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| 1.8601 | 4.22 | 1100 | 0.9262 | 0.7385 | 0.7627 | 0.7385 | 0.7190 | 0.8170 |
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| 84 |
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| 1.8601 | 4.41 | 1150 | 0.9209 | 0.7385 | 0.7586 | 0.7385 | 0.7221 | 0.8170 |
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| 85 |
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| 1.8601 | 4.6 | 1200 | 0.9163 | 0.7520 | 0.8027 | 0.7520 | 0.7416 | 0.8280 |
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| 86 |
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| 1.8601 | 4.79 | 1250 | 0.7954 | 0.8140 | 0.8394 | 0.8140 | 0.8028 | 0.8682 |
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| 87 |
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| 1.8601 | 4.99 | 1300 | 0.8244 | 0.7709 | 0.7999 | 0.7709 | 0.7651 | 0.8388 |
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| 88 |
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| 1.624 | 5.18 | 1350 | 0.8025 | 0.7655 | 0.8100 | 0.7655 | 0.7599 | 0.8364 |
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| 89 |
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| 1.624 | 5.37 | 1400 | 0.7521 | 0.7925 | 0.8238 | 0.7925 | 0.7827 | 0.8558 |
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| 90 |
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| 1.624 | 5.56 | 1450 | 0.7821 | 0.7898 | 0.8231 | 0.7898 | 0.7824 | 0.8528 |
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| 91 |
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| 1.624 | 5.75 | 1500 | 0.6841 | 0.7951 | 0.8237 | 0.7951 | 0.7887 | 0.8577 |
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| 92 |
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| 1.624 | 5.94 | 1550 | 0.6757 | 0.7978 | 0.8276 | 0.7978 | 0.7935 | 0.8596 |
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| 93 |
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| 1.4343 | 6.14 | 1600 | 0.6709 | 0.8140 | 0.8415 | 0.8140 | 0.8094 | 0.8709 |
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| 94 |
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| 1.4343 | 6.33 | 1650 | 0.6361 | 0.8113 | 0.8364 | 0.8113 | 0.8045 | 0.8690 |
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| 95 |
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| 1.4343 | 6.52 | 1700 | 0.6413 | 0.8275 | 0.8479 | 0.8275 | 0.8231 | 0.8814 |
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| 96 |
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| 1.4343 | 6.71 | 1750 | 0.6074 | 0.8302 | 0.8484 | 0.8302 | 0.8244 | 0.8803 |
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| 97 |
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| 1.4343 | 6.9 | 1800 | 0.6286 | 0.8005 | 0.8321 | 0.8005 | 0.7964 | 0.8606 |
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| 1.3175 | 7.09 | 1850 | 0.5431 | 0.8356 | 0.8558 | 0.8356 | 0.8312 | 0.8860 |
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| 1.3175 | 7.29 | 1900 | 0.5612 | 0.8491 | 0.8828 | 0.8491 | 0.8499 | 0.8927 |
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| 100 |
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| 1.3175 | 7.48 | 1950 | 0.5324 | 0.8491 | 0.8795 | 0.8491 | 0.8492 | 0.8954 |
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| 101 |
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| 1.3175 | 7.67 | 2000 | 0.5793 | 0.8383 | 0.8589 | 0.8383 | 0.8345 | 0.8871 |
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| 102 |
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| 1.3175 | 7.86 | 2050 | 0.5722 | 0.8248 | 0.8575 | 0.8248 | 0.8258 | 0.8757 |
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| 103 |
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| 1.2154 | 8.05 | 2100 | 0.6362 | 0.8167 | 0.8511 | 0.8167 | 0.8149 | 0.8701 |
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| 104 |
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| 1.2154 | 8.25 | 2150 | 0.5846 | 0.8302 | 0.8588 | 0.8302 | 0.8293 | 0.8814 |
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| 105 |
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| 1.2154 | 8.44 | 2200 | 0.6121 | 0.8113 | 0.8477 | 0.8113 | 0.8065 | 0.8704 |
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| 106 |
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| 1.2154 | 8.63 | 2250 | 0.5895 | 0.8356 | 0.8671 | 0.8356 | 0.8343 | 0.8871 |
|
| 107 |
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| 1.2154 | 8.82 | 2300 | 0.5404 | 0.8437 | 0.8756 | 0.8437 | 0.8407 | 0.8927 |
|
| 108 |
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| 1.1306 | 9.01 | 2350 | 0.5433 | 0.8410 | 0.8657 | 0.8410 | 0.8394 | 0.8900 |
|
| 109 |
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| 1.1306 | 9.2 | 2400 | 0.5535 | 0.8383 | 0.8645 | 0.8383 | 0.8380 | 0.8881 |
|
| 110 |
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| 1.1306 | 9.4 | 2450 | 0.5201 | 0.8518 | 0.8850 | 0.8518 | 0.8518 | 0.8957 |
|
| 111 |
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| 1.1306 | 9.59 | 2500 | 0.5464 | 0.8383 | 0.8680 | 0.8383 | 0.8373 | 0.8881 |
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| 112 |
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| 1.1306 | 9.78 | 2550 | 0.5960 | 0.8329 | 0.8586 | 0.8329 | 0.8304 | 0.8841 |
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| 113 |
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| 1.1306 | 9.97 | 2600 | 0.5304 | 0.8518 | 0.8790 | 0.8518 | 0.8506 | 0.8957 |
|
| 114 |
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| 1.0743 | 10.16 | 2650 | 0.4804 | 0.8706 | 0.8937 | 0.8706 | 0.8703 | 0.9086 |
|
| 115 |
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| 1.0743 | 10.35 | 2700 | 0.5004 | 0.8652 | 0.8908 | 0.8652 | 0.8640 | 0.9059 |
|
| 116 |
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| 1.0743 | 10.55 | 2750 | 0.4730 | 0.8652 | 0.8921 | 0.8652 | 0.8643 | 0.9070 |
|
| 117 |
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| 1.0743 | 10.74 | 2800 | 0.4958 | 0.8383 | 0.8663 | 0.8383 | 0.8372 | 0.8879 |
|
| 118 |
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| 1.0743 | 10.93 | 2850 | 0.4672 | 0.8544 | 0.8814 | 0.8544 | 0.8538 | 0.8973 |
|
| 119 |
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| 1.0274 | 11.12 | 2900 | 0.5339 | 0.8571 | 0.8807 | 0.8571 | 0.8565 | 0.9003 |
|
| 120 |
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| 1.0274 | 11.31 | 2950 | 0.5013 | 0.8491 | 0.8698 | 0.8491 | 0.8462 | 0.8954 |
|
| 121 |
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| 1.0274 | 11.51 | 3000 | 0.4882 | 0.8679 | 0.8904 | 0.8679 | 0.8677 | 0.9078 |
|
| 122 |
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| 1.0274 | 11.7 | 3050 | 0.5059 | 0.8518 | 0.8837 | 0.8518 | 0.8519 | 0.8965 |
|
| 123 |
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| 1.0274 | 11.89 | 3100 | 0.4636 | 0.8679 | 0.8864 | 0.8679 | 0.8666 | 0.9075 |
|
| 124 |
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| 0.9585 | 12.08 | 3150 | 0.4667 | 0.8787 | 0.8955 | 0.8787 | 0.8776 | 0.9143 |
|
| 125 |
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| 0.9585 | 12.27 | 3200 | 0.5159 | 0.8544 | 0.8734 | 0.8544 | 0.8534 | 0.8976 |
|
| 126 |
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| 0.9585 | 12.46 | 3250 | 0.5177 | 0.8518 | 0.8748 | 0.8518 | 0.8528 | 0.8987 |
|
| 127 |
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| 0.9585 | 12.66 | 3300 | 0.4435 | 0.8841 | 0.9040 | 0.8841 | 0.8835 | 0.9189 |
|
| 128 |
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| 0.9585 | 12.85 | 3350 | 0.5116 | 0.8544 | 0.8851 | 0.8544 | 0.8558 | 0.8992 |
|
| 129 |
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| 0.9352 | 13.04 | 3400 | 0.4538 | 0.8706 | 0.8888 | 0.8706 | 0.8697 | 0.9105 |
|
| 130 |
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| 0.9352 | 13.23 | 3450 | 0.4973 | 0.8706 | 0.8944 | 0.8706 | 0.8684 | 0.9086 |
|
| 131 |
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| 0.9352 | 13.42 | 3500 | 0.4465 | 0.8760 | 0.8937 | 0.8760 | 0.8741 | 0.9135 |
|
| 132 |
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| 0.9352 | 13.61 | 3550 | 0.4691 | 0.8814 | 0.9042 | 0.8814 | 0.8806 | 0.9154 |
|
| 133 |
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| 0.9352 | 13.81 | 3600 | 0.5010 | 0.8652 | 0.8916 | 0.8652 | 0.8641 | 0.9051 |
|
| 134 |
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| 0.9352 | 14.0 | 3650 | 0.5133 | 0.8410 | 0.8728 | 0.8410 | 0.8396 | 0.8879 |
|
| 135 |
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| 0.8941 | 14.19 | 3700 | 0.4476 | 0.8706 | 0.8961 | 0.8706 | 0.8729 | 0.9086 |
|
| 136 |
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| 0.8941 | 14.38 | 3750 | 0.4321 | 0.8679 | 0.8915 | 0.8679 | 0.8681 | 0.9067 |
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| 137 |
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| 0.8941 | 14.57 | 3800 | 0.4033 | 0.8841 | 0.8991 | 0.8841 | 0.8835 | 0.9181 |
|
| 138 |
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| 0.8941 | 14.77 | 3850 | 0.4599 | 0.8841 | 0.9052 | 0.8841 | 0.8827 | 0.9181 |
|
| 139 |
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| 0.8941 | 14.96 | 3900 | 0.4673 | 0.8625 | 0.8883 | 0.8625 | 0.8631 | 0.9040 |
|
| 140 |
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| 0.8574 | 15.15 | 3950 | 0.4906 | 0.8760 | 0.8993 | 0.8760 | 0.8749 | 0.9135 |
|
| 141 |
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| 0.8574 | 15.34 | 4000 | 0.5055 | 0.8544 | 0.8836 | 0.8544 | 0.8518 | 0.8984 |
|
| 142 |
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| 0.8574 | 15.53 | 4050 | 0.4119 | 0.8841 | 0.8985 | 0.8841 | 0.8831 | 0.9191 |
|
| 143 |
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| 0.8574 | 15.72 | 4100 | 0.4684 | 0.8760 | 0.8989 | 0.8760 | 0.8752 | 0.9135 |
|
| 144 |
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| 0.8574 | 15.92 | 4150 | 0.4453 | 0.8787 | 0.8999 | 0.8787 | 0.8776 | 0.9151 |
|
| 145 |
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| 0.8344 | 16.11 | 4200 | 0.4928 | 0.8787 | 0.9000 | 0.8787 | 0.8783 | 0.9143 |
|
| 146 |
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| 0.8344 | 16.3 | 4250 | 0.4535 | 0.8868 | 0.9067 | 0.8868 | 0.8863 | 0.9191 |
|
| 147 |
+
| 0.8344 | 16.49 | 4300 | 0.4259 | 0.8787 | 0.8986 | 0.8787 | 0.8781 | 0.9154 |
|
| 148 |
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| 0.8344 | 16.68 | 4350 | 0.4289 | 0.8787 | 0.8970 | 0.8787 | 0.8784 | 0.9154 |
|
| 149 |
+
| 0.8344 | 16.87 | 4400 | 0.4828 | 0.8814 | 0.9013 | 0.8814 | 0.8813 | 0.9154 |
|
| 150 |
+
| 0.8066 | 17.07 | 4450 | 0.4866 | 0.8787 | 0.8969 | 0.8787 | 0.8792 | 0.9135 |
|
| 151 |
+
| 0.8066 | 17.26 | 4500 | 0.4388 | 0.8760 | 0.8934 | 0.8760 | 0.8768 | 0.9116 |
|
| 152 |
+
| 0.8066 | 17.45 | 4550 | 0.5018 | 0.8787 | 0.8993 | 0.8787 | 0.8775 | 0.9143 |
|
| 153 |
+
| 0.8066 | 17.64 | 4600 | 0.4838 | 0.8814 | 0.8981 | 0.8814 | 0.8808 | 0.9154 |
|
| 154 |
+
| 0.8066 | 17.83 | 4650 | 0.5394 | 0.8679 | 0.8893 | 0.8679 | 0.8662 | 0.9059 |
|
| 155 |
+
| 0.7757 | 18.02 | 4700 | 0.4628 | 0.8814 | 0.8964 | 0.8814 | 0.8800 | 0.9162 |
|
| 156 |
+
| 0.7757 | 18.22 | 4750 | 0.5456 | 0.8733 | 0.8907 | 0.8733 | 0.8719 | 0.9097 |
|
| 157 |
+
| 0.7757 | 18.41 | 4800 | 0.4858 | 0.8814 | 0.8970 | 0.8814 | 0.8804 | 0.9154 |
|
| 158 |
+
| 0.7757 | 18.6 | 4850 | 0.5836 | 0.8571 | 0.8776 | 0.8571 | 0.8568 | 0.8984 |
|
| 159 |
+
| 0.7757 | 18.79 | 4900 | 0.5008 | 0.8787 | 0.8985 | 0.8787 | 0.8781 | 0.9143 |
|
| 160 |
+
| 0.7757 | 18.98 | 4950 | 0.5259 | 0.8760 | 0.8950 | 0.8760 | 0.8749 | 0.9116 |
|
| 161 |
+
| 0.7595 | 19.18 | 5000 | 0.5906 | 0.8652 | 0.8869 | 0.8652 | 0.8657 | 0.9040 |
|
| 162 |
+
| 0.7595 | 19.37 | 5050 | 0.4905 | 0.8841 | 0.8993 | 0.8841 | 0.8839 | 0.9173 |
|
| 163 |
+
| 0.7595 | 19.56 | 5100 | 0.5958 | 0.8598 | 0.8804 | 0.8598 | 0.8596 | 0.9003 |
|
| 164 |
+
| 0.7595 | 19.75 | 5150 | 0.5466 | 0.8679 | 0.8924 | 0.8679 | 0.8666 | 0.9059 |
|
| 165 |
+
| 0.7595 | 19.94 | 5200 | 0.4639 | 0.8841 | 0.9008 | 0.8841 | 0.8834 | 0.9173 |
|
| 166 |
+
| 0.7257 | 20.13 | 5250 | 0.5094 | 0.8787 | 0.9015 | 0.8787 | 0.8795 | 0.9135 |
|
| 167 |
+
| 0.7257 | 20.33 | 5300 | 0.5310 | 0.8733 | 0.8973 | 0.8733 | 0.8737 | 0.9097 |
|
| 168 |
+
| 0.7257 | 20.52 | 5350 | 0.5118 | 0.8733 | 0.8925 | 0.8733 | 0.8734 | 0.9097 |
|
| 169 |
+
| 0.7257 | 20.71 | 5400 | 0.5166 | 0.8814 | 0.9017 | 0.8814 | 0.8814 | 0.9154 |
|
| 170 |
+
| 0.7257 | 20.9 | 5450 | 0.4850 | 0.8814 | 0.8984 | 0.8814 | 0.8807 | 0.9164 |
|
| 171 |
+
| 0.7185 | 21.09 | 5500 | 0.5161 | 0.8841 | 0.9018 | 0.8841 | 0.8842 | 0.9183 |
|
| 172 |
+
| 0.7185 | 21.28 | 5550 | 0.5197 | 0.8706 | 0.8904 | 0.8706 | 0.8694 | 0.9086 |
|
| 173 |
+
| 0.7185 | 21.48 | 5600 | 0.5297 | 0.8733 | 0.8921 | 0.8733 | 0.8728 | 0.9097 |
|
| 174 |
+
| 0.7185 | 21.67 | 5650 | 0.5317 | 0.8706 | 0.8913 | 0.8706 | 0.8694 | 0.9078 |
|
| 175 |
+
| 0.7185 | 21.86 | 5700 | 0.5120 | 0.8625 | 0.8809 | 0.8625 | 0.8610 | 0.9022 |
|
| 176 |
+
| 0.6968 | 22.05 | 5750 | 0.5144 | 0.8760 | 0.8960 | 0.8760 | 0.8753 | 0.9116 |
|
| 177 |
+
| 0.6968 | 22.24 | 5800 | 0.5688 | 0.8733 | 0.8911 | 0.8733 | 0.8721 | 0.9097 |
|
| 178 |
+
| 0.6968 | 22.44 | 5850 | 0.5430 | 0.8733 | 0.8916 | 0.8733 | 0.8724 | 0.9097 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 179 |
|
| 180 |
|
| 181 |
### Framework versions
|
runs/Jun28_02-49-38_LAPTOP-1GID9RGH/events.out.tfevents.1719517779.LAPTOP-1GID9RGH.18912.2
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 sha256:0ddc5d850319ce40840f59364cc19412ffd5e116c090da9496da639eaa1271f5
|
| 3 |
+
size 75340
|
runs/Jun28_02-49-38_LAPTOP-1GID9RGH/events.out.tfevents.1719520475.LAPTOP-1GID9RGH.18912.3
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:fc6118548c0c6bbab7cca3656e15f9941ef27e15459668a8653bd7431623a4ae
|
| 3 |
+
size 610
|