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hubert-classifier-aug-fold-4

Audio Classification
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  1. README.md +93 -73
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README.md CHANGED
@@ -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: 0.5994
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- - Accuracy: 0.8908
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- - Precision: 0.9054
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- - Recall: 0.8908
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- - F1: 0.8902
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- - Binary: 0.9252
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  ## Model description
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@@ -60,73 +60,93 @@ 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 | 4.4211 | 0.0256 | 0.0066 | 0.0256 | 0.0094 | 0.2032 |
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- | No log | 0.27 | 100 | 4.3448 | 0.0499 | 0.0239 | 0.0499 | 0.0181 | 0.2625 |
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- | No log | 0.4 | 150 | 3.9589 | 0.1120 | 0.0582 | 0.1120 | 0.0534 | 0.3738 |
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- | No log | 0.54 | 200 | 3.6032 | 0.1727 | 0.0912 | 0.1727 | 0.0968 | 0.4177 |
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- | No log | 0.67 | 250 | 3.2149 | 0.2321 | 0.1419 | 0.2321 | 0.1452 | 0.4592 |
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- | No log | 0.81 | 300 | 2.8786 | 0.3441 | 0.2742 | 0.3441 | 0.2581 | 0.5387 |
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- | No log | 0.94 | 350 | 2.5253 | 0.4211 | 0.3438 | 0.4211 | 0.3380 | 0.5941 |
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- | 3.7437 | 1.08 | 400 | 2.1778 | 0.4588 | 0.4083 | 0.4588 | 0.3896 | 0.6201 |
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- | 3.7437 | 1.21 | 450 | 1.8620 | 0.5709 | 0.5259 | 0.5709 | 0.5166 | 0.6992 |
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- | 3.7437 | 1.35 | 500 | 1.6172 | 0.5803 | 0.5498 | 0.5803 | 0.5168 | 0.7062 |
73
- | 3.7437 | 1.48 | 550 | 1.3691 | 0.6640 | 0.6471 | 0.6640 | 0.6287 | 0.7633 |
74
- | 3.7437 | 1.62 | 600 | 1.2425 | 0.6910 | 0.6704 | 0.6910 | 0.6541 | 0.7837 |
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- | 3.7437 | 1.75 | 650 | 1.1155 | 0.7193 | 0.7205 | 0.7193 | 0.6936 | 0.8038 |
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- | 3.7437 | 1.89 | 700 | 0.9569 | 0.7463 | 0.7599 | 0.7463 | 0.7287 | 0.8225 |
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- | 1.7895 | 2.02 | 750 | 0.9260 | 0.7584 | 0.7657 | 0.7584 | 0.7389 | 0.8321 |
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- | 1.7895 | 2.16 | 800 | 0.8667 | 0.7787 | 0.8008 | 0.7787 | 0.7639 | 0.8452 |
79
- | 1.7895 | 2.29 | 850 | 0.7438 | 0.8138 | 0.8159 | 0.8138 | 0.8047 | 0.8696 |
80
- | 1.7895 | 2.43 | 900 | 0.7958 | 0.8016 | 0.8175 | 0.8016 | 0.7917 | 0.8602 |
81
- | 1.7895 | 2.56 | 950 | 0.6627 | 0.8327 | 0.8449 | 0.8327 | 0.8296 | 0.8829 |
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- | 1.7895 | 2.7 | 1000 | 0.7242 | 0.7976 | 0.8152 | 0.7976 | 0.7882 | 0.8592 |
83
- | 1.7895 | 2.83 | 1050 | 0.6745 | 0.8165 | 0.8337 | 0.8165 | 0.8123 | 0.8719 |
84
- | 1.7895 | 2.96 | 1100 | 0.6795 | 0.8192 | 0.8388 | 0.8192 | 0.8158 | 0.8761 |
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- | 1.0205 | 3.1 | 1150 | 0.6546 | 0.8354 | 0.8575 | 0.8354 | 0.8319 | 0.8835 |
86
- | 1.0205 | 3.23 | 1200 | 0.6165 | 0.8394 | 0.8489 | 0.8394 | 0.8365 | 0.8868 |
87
- | 1.0205 | 3.37 | 1250 | 0.7041 | 0.8232 | 0.8490 | 0.8232 | 0.8202 | 0.8775 |
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- | 1.0205 | 3.5 | 1300 | 0.5767 | 0.8516 | 0.8626 | 0.8516 | 0.8485 | 0.8957 |
89
- | 1.0205 | 3.64 | 1350 | 0.5831 | 0.8448 | 0.8609 | 0.8448 | 0.8404 | 0.8910 |
90
- | 1.0205 | 3.77 | 1400 | 0.5623 | 0.8650 | 0.8761 | 0.8650 | 0.8624 | 0.9051 |
91
- | 1.0205 | 3.91 | 1450 | 0.5696 | 0.8650 | 0.8757 | 0.8650 | 0.8630 | 0.9047 |
92
- | 0.7175 | 4.04 | 1500 | 0.5455 | 0.8543 | 0.8756 | 0.8543 | 0.8522 | 0.8981 |
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- | 0.7175 | 4.18 | 1550 | 0.5209 | 0.8650 | 0.8785 | 0.8650 | 0.8592 | 0.9053 |
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- | 0.7175 | 4.31 | 1600 | 0.6185 | 0.8435 | 0.8606 | 0.8435 | 0.8415 | 0.8908 |
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- | 0.7175 | 4.45 | 1650 | 0.5434 | 0.8677 | 0.8797 | 0.8677 | 0.8644 | 0.9066 |
96
- | 0.7175 | 4.58 | 1700 | 0.6622 | 0.8489 | 0.8728 | 0.8489 | 0.8444 | 0.8945 |
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- | 0.7175 | 4.72 | 1750 | 0.5668 | 0.8677 | 0.8798 | 0.8677 | 0.8662 | 0.9070 |
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- | 0.7175 | 4.85 | 1800 | 0.5375 | 0.8812 | 0.8934 | 0.8812 | 0.8804 | 0.9179 |
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- | 0.7175 | 4.99 | 1850 | 0.5550 | 0.8677 | 0.8780 | 0.8677 | 0.8640 | 0.9080 |
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- | 0.5694 | 5.12 | 1900 | 0.5739 | 0.8691 | 0.8811 | 0.8691 | 0.8647 | 0.9089 |
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- | 0.5694 | 5.26 | 1950 | 0.5325 | 0.8826 | 0.8923 | 0.8826 | 0.8818 | 0.9174 |
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- | 0.5694 | 5.39 | 2000 | 0.5496 | 0.8772 | 0.8885 | 0.8772 | 0.8747 | 0.9147 |
103
- | 0.5694 | 5.53 | 2050 | 0.6038 | 0.8745 | 0.8854 | 0.8745 | 0.8726 | 0.9123 |
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- | 0.5694 | 5.66 | 2100 | 0.5606 | 0.8826 | 0.8936 | 0.8826 | 0.8816 | 0.9194 |
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- | 0.5694 | 5.8 | 2150 | 0.5655 | 0.8745 | 0.8885 | 0.8745 | 0.8741 | 0.9128 |
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- | 0.5694 | 5.93 | 2200 | 0.5588 | 0.8785 | 0.8912 | 0.8785 | 0.8775 | 0.9157 |
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- | 0.4761 | 6.06 | 2250 | 0.6021 | 0.8637 | 0.8802 | 0.8637 | 0.8617 | 0.9047 |
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- | 0.4761 | 6.2 | 2300 | 0.5785 | 0.8839 | 0.8956 | 0.8839 | 0.8840 | 0.9194 |
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- | 0.4761 | 6.33 | 2350 | 0.6397 | 0.8691 | 0.8831 | 0.8691 | 0.8677 | 0.9090 |
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- | 0.4761 | 6.47 | 2400 | 0.5376 | 0.8880 | 0.8998 | 0.8880 | 0.8866 | 0.9238 |
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- | 0.4761 | 6.6 | 2450 | 0.5669 | 0.8920 | 0.9025 | 0.8920 | 0.8904 | 0.9255 |
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- | 0.4761 | 6.74 | 2500 | 0.6968 | 0.8543 | 0.8723 | 0.8543 | 0.8522 | 0.8987 |
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- | 0.4761 | 6.87 | 2550 | 0.5628 | 0.8839 | 0.8952 | 0.8839 | 0.8829 | 0.9194 |
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- | 0.4178 | 7.01 | 2600 | 0.5975 | 0.8772 | 0.8861 | 0.8772 | 0.8755 | 0.9167 |
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- | 0.4178 | 7.14 | 2650 | 0.5967 | 0.8853 | 0.8919 | 0.8853 | 0.8834 | 0.9219 |
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- | 0.4178 | 7.28 | 2700 | 0.6271 | 0.8799 | 0.8921 | 0.8799 | 0.8783 | 0.9166 |
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- | 0.4178 | 7.41 | 2750 | 0.6047 | 0.8799 | 0.8916 | 0.8799 | 0.8784 | 0.9170 |
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- | 0.4178 | 7.55 | 2800 | 0.5336 | 0.8853 | 0.8978 | 0.8853 | 0.8829 | 0.9204 |
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- | 0.4178 | 7.68 | 2850 | 0.5722 | 0.8988 | 0.9097 | 0.8988 | 0.8988 | 0.9298 |
120
- | 0.4178 | 7.82 | 2900 | 0.5478 | 0.8866 | 0.8987 | 0.8866 | 0.8853 | 0.9213 |
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- | 0.4178 | 7.95 | 2950 | 0.5176 | 0.8907 | 0.9016 | 0.8907 | 0.8897 | 0.9242 |
122
- | 0.3642 | 8.09 | 3000 | 0.5172 | 0.8947 | 0.9030 | 0.8947 | 0.8938 | 0.9279 |
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- | 0.3642 | 8.22 | 3050 | 0.6341 | 0.8799 | 0.8932 | 0.8799 | 0.8787 | 0.9157 |
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- | 0.3642 | 8.36 | 3100 | 0.6011 | 0.8812 | 0.8897 | 0.8812 | 0.8797 | 0.9181 |
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- | 0.3642 | 8.49 | 3150 | 0.5807 | 0.8745 | 0.8864 | 0.8745 | 0.8733 | 0.9132 |
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- | 0.3642 | 8.63 | 3200 | 0.5931 | 0.8799 | 0.8942 | 0.8799 | 0.8795 | 0.9157 |
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- | 0.3642 | 8.76 | 3250 | 0.6045 | 0.8812 | 0.8955 | 0.8812 | 0.8818 | 0.9175 |
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- | 0.3642 | 8.89 | 3300 | 0.5473 | 0.8934 | 0.9047 | 0.8934 | 0.8927 | 0.9260 |
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- | 0.3326 | 9.03 | 3350 | 0.5111 | 0.8934 | 0.9058 | 0.8934 | 0.8924 | 0.9266 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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: 0.6864
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+ - Accuracy: 0.8612
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+ - Precision: 0.8735
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+ - Recall: 0.8612
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+ - F1: 0.8606
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+ - Binary: 0.9026
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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 | 0.24 | 50 | 4.4183 | 0.0135 | 0.0052 | 0.0135 | 0.0050 | 0.1206 |
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+ | No log | 0.48 | 100 | 4.2895 | 0.0412 | 0.0103 | 0.0412 | 0.0108 | 0.2549 |
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+ | No log | 0.72 | 150 | 3.9961 | 0.0592 | 0.0278 | 0.0592 | 0.0286 | 0.3335 |
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+ | No log | 0.96 | 200 | 3.7039 | 0.0742 | 0.0345 | 0.0742 | 0.0283 | 0.3461 |
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+ | 4.2414 | 1.2 | 250 | 3.4082 | 0.1394 | 0.0770 | 0.1394 | 0.0791 | 0.3938 |
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+ | 4.2414 | 1.44 | 300 | 3.1852 | 0.1979 | 0.1003 | 0.1979 | 0.1107 | 0.4377 |
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+ | 4.2414 | 1.68 | 350 | 2.9114 | 0.2976 | 0.2089 | 0.2976 | 0.2077 | 0.5074 |
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+ | 4.2414 | 1.92 | 400 | 2.5996 | 0.3366 | 0.2524 | 0.3366 | 0.2461 | 0.5348 |
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+ | 3.2619 | 2.16 | 450 | 2.3085 | 0.4100 | 0.3088 | 0.4100 | 0.3208 | 0.5857 |
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+ | 3.2619 | 2.4 | 500 | 2.0470 | 0.4873 | 0.4303 | 0.4873 | 0.4151 | 0.6394 |
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+ | 3.2619 | 2.63 | 550 | 1.7979 | 0.5307 | 0.4934 | 0.5307 | 0.4713 | 0.6713 |
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+ | 3.2619 | 2.87 | 600 | 1.5495 | 0.6012 | 0.5736 | 0.6012 | 0.5519 | 0.7199 |
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+ | 2.2861 | 3.11 | 650 | 1.4334 | 0.6124 | 0.6399 | 0.6124 | 0.5690 | 0.7302 |
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+ | 2.2861 | 3.35 | 700 | 1.3103 | 0.6544 | 0.6847 | 0.6544 | 0.6231 | 0.7576 |
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+ | 2.2861 | 3.59 | 750 | 1.1635 | 0.6927 | 0.7090 | 0.6927 | 0.6698 | 0.7849 |
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+ | 2.2861 | 3.83 | 800 | 1.0149 | 0.7549 | 0.7708 | 0.7549 | 0.7481 | 0.8289 |
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+ | 1.5996 | 4.07 | 850 | 1.0088 | 0.7286 | 0.7489 | 0.7286 | 0.7069 | 0.8106 |
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+ | 1.5996 | 4.31 | 900 | 0.8567 | 0.7699 | 0.7719 | 0.7699 | 0.7540 | 0.8398 |
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+ | 1.5996 | 4.55 | 950 | 0.8231 | 0.7916 | 0.8071 | 0.7916 | 0.7830 | 0.8552 |
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+ | 1.5996 | 4.79 | 1000 | 0.8333 | 0.7841 | 0.8041 | 0.7841 | 0.7754 | 0.8489 |
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+ | 1.2436 | 5.03 | 1050 | 0.7799 | 0.7946 | 0.8084 | 0.7946 | 0.7884 | 0.8562 |
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+ | 1.2436 | 5.27 | 1100 | 0.7429 | 0.7946 | 0.8097 | 0.7946 | 0.7917 | 0.8568 |
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+ | 1.2436 | 5.51 | 1150 | 0.7050 | 0.8238 | 0.8384 | 0.8238 | 0.8202 | 0.8772 |
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+ | 1.2436 | 5.75 | 1200 | 0.6639 | 0.8193 | 0.8251 | 0.8193 | 0.8139 | 0.8738 |
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+ | 1.2436 | 5.99 | 1250 | 0.6918 | 0.8186 | 0.8387 | 0.8186 | 0.8141 | 0.8740 |
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+ | 1.0055 | 6.23 | 1300 | 0.6296 | 0.8246 | 0.8383 | 0.8246 | 0.8186 | 0.8768 |
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+ | 1.0055 | 6.47 | 1350 | 0.6581 | 0.8253 | 0.8412 | 0.8253 | 0.8215 | 0.8779 |
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+ | 1.0055 | 6.71 | 1400 | 0.6302 | 0.8313 | 0.8469 | 0.8313 | 0.8292 | 0.8821 |
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+ | 1.0055 | 6.95 | 1450 | 0.5998 | 0.8448 | 0.8593 | 0.8448 | 0.8420 | 0.8906 |
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+ | 0.8805 | 7.19 | 1500 | 0.6230 | 0.8456 | 0.8531 | 0.8456 | 0.8443 | 0.8926 |
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+ | 0.8805 | 7.43 | 1550 | 0.6308 | 0.8396 | 0.8528 | 0.8396 | 0.8377 | 0.8887 |
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+ | 0.8805 | 7.66 | 1600 | 0.5979 | 0.8418 | 0.8531 | 0.8418 | 0.8413 | 0.8897 |
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+ | 0.8805 | 7.9 | 1650 | 0.6022 | 0.8478 | 0.8616 | 0.8478 | 0.8469 | 0.8946 |
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+ | 0.7681 | 8.14 | 1700 | 0.5872 | 0.8471 | 0.8573 | 0.8471 | 0.8453 | 0.8927 |
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+ | 0.7681 | 8.38 | 1750 | 0.5744 | 0.8433 | 0.8570 | 0.8433 | 0.8420 | 0.8909 |
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+ | 0.7681 | 8.62 | 1800 | 0.5351 | 0.8643 | 0.8707 | 0.8643 | 0.8627 | 0.9061 |
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+ | 0.7681 | 8.86 | 1850 | 0.5688 | 0.8561 | 0.8680 | 0.8561 | 0.8559 | 0.8990 |
100
+ | 0.7001 | 9.1 | 1900 | 0.6618 | 0.8298 | 0.8457 | 0.8298 | 0.8269 | 0.8810 |
101
+ | 0.7001 | 9.34 | 1950 | 0.6244 | 0.8426 | 0.8571 | 0.8426 | 0.8422 | 0.8900 |
102
+ | 0.7001 | 9.58 | 2000 | 0.5802 | 0.8576 | 0.8681 | 0.8576 | 0.8569 | 0.8996 |
103
+ | 0.7001 | 9.82 | 2050 | 0.5352 | 0.8688 | 0.8761 | 0.8688 | 0.8687 | 0.9072 |
104
+ | 0.6288 | 10.06 | 2100 | 0.5347 | 0.8651 | 0.8773 | 0.8651 | 0.8637 | 0.9049 |
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+ | 0.6288 | 10.3 | 2150 | 0.6019 | 0.8546 | 0.8665 | 0.8546 | 0.8535 | 0.8986 |
106
+ | 0.6288 | 10.54 | 2200 | 0.5699 | 0.8598 | 0.8670 | 0.8598 | 0.8571 | 0.9005 |
107
+ | 0.6288 | 10.78 | 2250 | 0.5494 | 0.8748 | 0.8838 | 0.8748 | 0.8730 | 0.9118 |
108
+ | 0.5959 | 11.02 | 2300 | 0.5471 | 0.8718 | 0.8804 | 0.8718 | 0.8714 | 0.9103 |
109
+ | 0.5959 | 11.26 | 2350 | 0.5570 | 0.8628 | 0.8738 | 0.8628 | 0.8605 | 0.9042 |
110
+ | 0.5959 | 11.5 | 2400 | 0.5300 | 0.8801 | 0.8875 | 0.8801 | 0.8791 | 0.9163 |
111
+ | 0.5959 | 11.74 | 2450 | 0.5418 | 0.8643 | 0.8725 | 0.8643 | 0.8630 | 0.9039 |
112
+ | 0.5959 | 11.98 | 2500 | 0.5418 | 0.8726 | 0.8822 | 0.8726 | 0.8715 | 0.9108 |
113
+ | 0.5407 | 12.22 | 2550 | 0.5718 | 0.8658 | 0.8755 | 0.8658 | 0.8652 | 0.9058 |
114
+ | 0.5407 | 12.46 | 2600 | 0.5686 | 0.8658 | 0.8725 | 0.8658 | 0.8643 | 0.9058 |
115
+ | 0.5407 | 12.69 | 2650 | 0.6045 | 0.8658 | 0.8768 | 0.8658 | 0.8656 | 0.9053 |
116
+ | 0.5407 | 12.93 | 2700 | 0.5571 | 0.8621 | 0.8715 | 0.8621 | 0.8607 | 0.9027 |
117
+ | 0.5175 | 13.17 | 2750 | 0.5367 | 0.8756 | 0.8809 | 0.8756 | 0.8745 | 0.9131 |
118
+ | 0.5175 | 13.41 | 2800 | 0.5241 | 0.8771 | 0.8827 | 0.8771 | 0.8755 | 0.9142 |
119
+ | 0.5175 | 13.65 | 2850 | 0.5793 | 0.8703 | 0.8792 | 0.8703 | 0.8691 | 0.9095 |
120
+ | 0.5175 | 13.89 | 2900 | 0.5608 | 0.8756 | 0.8843 | 0.8756 | 0.8751 | 0.9123 |
121
+ | 0.4913 | 14.13 | 2950 | 0.5734 | 0.8711 | 0.8781 | 0.8711 | 0.8694 | 0.9100 |
122
+ | 0.4913 | 14.37 | 3000 | 0.5916 | 0.8771 | 0.8821 | 0.8771 | 0.8758 | 0.9134 |
123
+ | 0.4913 | 14.61 | 3050 | 0.5651 | 0.8696 | 0.8761 | 0.8696 | 0.8680 | 0.9082 |
124
+ | 0.4913 | 14.85 | 3100 | 0.5535 | 0.8786 | 0.8831 | 0.8786 | 0.8771 | 0.9152 |
125
+ | 0.4747 | 15.09 | 3150 | 0.5694 | 0.8741 | 0.8819 | 0.8741 | 0.8737 | 0.9118 |
126
+ | 0.4747 | 15.33 | 3200 | 0.5759 | 0.8726 | 0.8794 | 0.8726 | 0.8720 | 0.9103 |
127
+ | 0.4747 | 15.57 | 3250 | 0.5827 | 0.8666 | 0.8718 | 0.8666 | 0.8642 | 0.9070 |
128
+ | 0.4747 | 15.81 | 3300 | 0.5497 | 0.8763 | 0.8838 | 0.8763 | 0.8758 | 0.9139 |
129
+ | 0.4456 | 16.05 | 3350 | 0.5757 | 0.8838 | 0.8896 | 0.8838 | 0.8835 | 0.9192 |
130
+ | 0.4456 | 16.29 | 3400 | 0.5547 | 0.8756 | 0.8830 | 0.8756 | 0.8731 | 0.9123 |
131
+ | 0.4456 | 16.53 | 3450 | 0.5431 | 0.8808 | 0.8883 | 0.8808 | 0.8801 | 0.9168 |
132
+ | 0.4456 | 16.77 | 3500 | 0.5459 | 0.8823 | 0.8883 | 0.8823 | 0.8815 | 0.9175 |
133
+ | 0.4248 | 17.01 | 3550 | 0.5111 | 0.8891 | 0.8947 | 0.8891 | 0.8878 | 0.9220 |
134
+ | 0.4248 | 17.25 | 3600 | 0.5371 | 0.8868 | 0.8922 | 0.8868 | 0.8860 | 0.9207 |
135
+ | 0.4248 | 17.49 | 3650 | 0.5757 | 0.8748 | 0.8843 | 0.8748 | 0.8745 | 0.9131 |
136
+ | 0.4248 | 17.72 | 3700 | 0.5509 | 0.8816 | 0.8880 | 0.8816 | 0.8804 | 0.9168 |
137
+ | 0.4248 | 17.96 | 3750 | 0.5166 | 0.8853 | 0.8911 | 0.8853 | 0.8845 | 0.9197 |
138
+ | 0.405 | 18.2 | 3800 | 0.5392 | 0.8823 | 0.8881 | 0.8823 | 0.8814 | 0.9173 |
139
+ | 0.405 | 18.44 | 3850 | 0.5357 | 0.8793 | 0.8857 | 0.8793 | 0.8784 | 0.9155 |
140
+ | 0.405 | 18.68 | 3900 | 0.5564 | 0.8748 | 0.8808 | 0.8748 | 0.8739 | 0.9120 |
141
+ | 0.405 | 18.92 | 3950 | 0.5377 | 0.8853 | 0.8898 | 0.8853 | 0.8842 | 0.9202 |
142
+ | 0.3925 | 19.16 | 4000 | 0.5489 | 0.8846 | 0.8902 | 0.8846 | 0.8832 | 0.9194 |
143
+ | 0.3925 | 19.4 | 4050 | 0.5953 | 0.8726 | 0.8800 | 0.8726 | 0.8713 | 0.9115 |
144
+ | 0.3925 | 19.64 | 4100 | 0.5802 | 0.8756 | 0.8812 | 0.8756 | 0.8738 | 0.9131 |
145
+ | 0.3925 | 19.88 | 4150 | 0.6130 | 0.8756 | 0.8827 | 0.8756 | 0.8743 | 0.9121 |
146
+ | 0.3707 | 20.12 | 4200 | 0.6210 | 0.8771 | 0.8828 | 0.8771 | 0.8760 | 0.9137 |
147
+ | 0.3707 | 20.36 | 4250 | 0.6460 | 0.8786 | 0.8849 | 0.8786 | 0.8774 | 0.9154 |
148
+ | 0.3707 | 20.6 | 4300 | 0.6255 | 0.8703 | 0.8780 | 0.8703 | 0.8694 | 0.9085 |
149
+ | 0.3707 | 20.84 | 4350 | 0.6773 | 0.8658 | 0.8739 | 0.8658 | 0.8653 | 0.9056 |
150
 
151
 
152
  ### Framework versions
runs/Jul26_03-43-39_LAPTOP-1GID9RGH/events.out.tfevents.1721940220.LAPTOP-1GID9RGH.7328.4 CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:01c3c35246783f3b6aff2d39a76174dd31f512e04a584318effe78c7484c6350
3
- size 54830
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0116a19ba3a754c4a4d329f76b23a2652ca63f285edb4901328d45ca9d0ee352
3
+ size 59260
runs/Jul26_03-43-39_LAPTOP-1GID9RGH/events.out.tfevents.1721942744.LAPTOP-1GID9RGH.7328.5 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:bab0dc0ea4a05b23b984071bb10ab893f0a43926cf727423d2332437e6a6e6f6
3
+ size 610