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Nugrahasetyaardi
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SER_model_xapiens

Audio Classification
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TensorBoard
Safetensors
wav2vec2
Generated from Trainer
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README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.6350
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- - Accuracy: 0.7167
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  ## Model description
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@@ -46,212 +46,112 @@ The following hyperparameters were used during training:
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 200
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 1 | 1.9415 | 0.7667 |
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- | No log | 2.0 | 2 | 2.0260 | 0.75 |
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- | No log | 3.0 | 3 | 2.1651 | 0.75 |
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- | No log | 4.0 | 4 | 2.2888 | 0.7333 |
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- | No log | 5.0 | 5 | 2.4043 | 0.7167 |
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- | No log | 6.0 | 6 | 2.4594 | 0.7167 |
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- | No log | 7.0 | 7 | 2.6252 | 0.7 |
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- | No log | 8.0 | 8 | 2.7498 | 0.7 |
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- | No log | 9.0 | 9 | 2.7988 | 0.7 |
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- | 0.0001 | 10.0 | 10 | 2.8114 | 0.7 |
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- | 0.0001 | 11.0 | 11 | 2.8079 | 0.7 |
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- | 0.0001 | 12.0 | 12 | 2.8016 | 0.7167 |
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- | 0.0001 | 13.0 | 13 | 2.8102 | 0.7 |
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- | 0.0001 | 14.0 | 14 | 2.8442 | 0.7 |
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- | 0.0001 | 15.0 | 15 | 2.8486 | 0.7 |
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- | 0.0001 | 16.0 | 16 | 2.8050 | 0.7 |
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- | 0.0001 | 17.0 | 17 | 2.7318 | 0.7167 |
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- | 0.0001 | 18.0 | 18 | 2.6570 | 0.7333 |
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- | 0.0001 | 19.0 | 19 | 2.6647 | 0.7167 |
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- | 0.0001 | 20.0 | 20 | 2.7293 | 0.7167 |
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- | 0.0001 | 21.0 | 21 | 2.7123 | 0.7167 |
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- | 0.0001 | 22.0 | 22 | 2.6657 | 0.7167 |
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- | 0.0001 | 23.0 | 23 | 2.5976 | 0.7 |
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- | 0.0001 | 24.0 | 24 | 2.5581 | 0.7167 |
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- | 0.0001 | 25.0 | 25 | 2.5381 | 0.7167 |
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- | 0.0001 | 26.0 | 26 | 2.5763 | 0.7167 |
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- | 0.0001 | 27.0 | 27 | 2.3864 | 0.7667 |
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- | 0.0001 | 28.0 | 28 | 2.4697 | 0.7167 |
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- | 0.0001 | 29.0 | 29 | 2.6195 | 0.7167 |
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- | 0.0058 | 30.0 | 30 | 2.7685 | 0.7 |
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- | 0.0058 | 31.0 | 31 | 2.9305 | 0.7 |
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- | 0.0058 | 32.0 | 32 | 2.9639 | 0.7 |
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- | 0.0058 | 33.0 | 33 | 2.7130 | 0.7 |
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- | 0.0058 | 34.0 | 34 | 2.7511 | 0.7 |
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- | 0.0058 | 35.0 | 35 | 2.7739 | 0.7167 |
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- | 0.0058 | 36.0 | 36 | 2.7640 | 0.7 |
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- | 0.0058 | 37.0 | 37 | 2.7995 | 0.7 |
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- | 0.0058 | 38.0 | 38 | 2.8741 | 0.7 |
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- | 0.0058 | 39.0 | 39 | 2.9037 | 0.6833 |
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- | 0.0088 | 40.0 | 40 | 2.9333 | 0.6833 |
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- | 0.0088 | 41.0 | 41 | 2.9276 | 0.7167 |
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- | 0.0088 | 42.0 | 42 | 2.8313 | 0.7 |
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- | 0.0088 | 43.0 | 43 | 2.7277 | 0.7333 |
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- | 0.0088 | 44.0 | 44 | 2.5530 | 0.7333 |
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- | 0.0088 | 45.0 | 45 | 2.5369 | 0.75 |
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- | 0.0088 | 46.0 | 46 | 2.4771 | 0.7667 |
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- | 0.0088 | 47.0 | 47 | 2.3890 | 0.75 |
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- | 0.0088 | 48.0 | 48 | 2.3417 | 0.75 |
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- | 0.0088 | 49.0 | 49 | 2.3213 | 0.75 |
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- | 0.0059 | 50.0 | 50 | 2.2189 | 0.7333 |
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- | 0.0059 | 51.0 | 51 | 2.2772 | 0.75 |
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- | 0.0059 | 52.0 | 52 | 2.6527 | 0.7 |
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- | 0.0059 | 53.0 | 53 | 2.7879 | 0.6667 |
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- | 0.0059 | 54.0 | 54 | 2.8742 | 0.6833 |
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- | 0.0059 | 55.0 | 55 | 2.9490 | 0.6833 |
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- | 0.0059 | 56.0 | 56 | 2.9270 | 0.6833 |
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- | 0.0059 | 57.0 | 57 | 2.9922 | 0.65 |
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- | 0.0059 | 58.0 | 58 | 3.2533 | 0.6333 |
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- | 0.0059 | 59.0 | 59 | 3.4309 | 0.6333 |
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- | 0.0064 | 60.0 | 60 | 3.5734 | 0.6167 |
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- | 0.0064 | 61.0 | 61 | 3.6463 | 0.6167 |
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- | 0.0064 | 62.0 | 62 | 3.4955 | 0.65 |
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- | 0.0064 | 63.0 | 63 | 3.4491 | 0.65 |
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- | 0.0064 | 64.0 | 64 | 3.4220 | 0.6333 |
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- | 0.0064 | 65.0 | 65 | 3.0787 | 0.6667 |
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- | 0.0064 | 66.0 | 66 | 2.7515 | 0.6833 |
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- | 0.0064 | 67.0 | 67 | 2.5267 | 0.7167 |
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- | 0.0064 | 68.0 | 68 | 2.5117 | 0.7 |
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- | 0.0064 | 69.0 | 69 | 2.6611 | 0.7 |
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- | 0.0051 | 70.0 | 70 | 2.7440 | 0.7167 |
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- | 0.0051 | 71.0 | 71 | 2.6501 | 0.7 |
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- | 0.0051 | 72.0 | 72 | 2.5473 | 0.7 |
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- | 0.0051 | 73.0 | 73 | 2.5388 | 0.7 |
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- | 0.0051 | 74.0 | 74 | 2.6984 | 0.7167 |
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- | 0.0051 | 75.0 | 75 | 2.6597 | 0.7167 |
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- | 0.0051 | 76.0 | 76 | 2.6281 | 0.7333 |
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- | 0.0051 | 77.0 | 77 | 2.5795 | 0.7333 |
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- | 0.0051 | 78.0 | 78 | 2.4916 | 0.7333 |
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- | 0.0051 | 79.0 | 79 | 2.4147 | 0.7667 |
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- | 0.0097 | 80.0 | 80 | 2.5416 | 0.75 |
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- | 0.0097 | 81.0 | 81 | 2.5719 | 0.75 |
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- | 0.0097 | 82.0 | 82 | 2.5790 | 0.7667 |
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- | 0.0097 | 83.0 | 83 | 2.5967 | 0.7667 |
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- | 0.0097 | 84.0 | 84 | 2.6306 | 0.7333 |
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- | 0.0097 | 85.0 | 85 | 2.6580 | 0.7167 |
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- | 0.0097 | 86.0 | 86 | 2.6966 | 0.7333 |
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- | 0.0097 | 87.0 | 87 | 2.7286 | 0.7333 |
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- | 0.0097 | 88.0 | 88 | 2.9644 | 0.6833 |
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- | 0.0097 | 89.0 | 89 | 3.2097 | 0.65 |
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- | 0.0063 | 90.0 | 90 | 3.4777 | 0.65 |
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- | 0.0063 | 91.0 | 91 | 3.3658 | 0.65 |
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- | 0.0063 | 92.0 | 92 | 3.1511 | 0.6833 |
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- | 0.0063 | 93.0 | 93 | 3.0925 | 0.6833 |
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- | 0.0063 | 94.0 | 94 | 3.0085 | 0.6833 |
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- | 0.0063 | 95.0 | 95 | 2.9864 | 0.6833 |
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- | 0.0063 | 96.0 | 96 | 2.9914 | 0.6833 |
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- | 0.0063 | 97.0 | 97 | 2.9962 | 0.6833 |
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- | 0.0063 | 98.0 | 98 | 2.9984 | 0.6833 |
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- | 0.0063 | 99.0 | 99 | 2.9746 | 0.7 |
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- | 0.0013 | 100.0 | 100 | 3.0042 | 0.7 |
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- | 0.0013 | 101.0 | 101 | 3.0111 | 0.7 |
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- | 0.0013 | 102.0 | 102 | 3.0132 | 0.7 |
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- | 0.0013 | 103.0 | 103 | 3.0107 | 0.7 |
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- | 0.0013 | 104.0 | 104 | 2.9891 | 0.7 |
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- | 0.0013 | 105.0 | 105 | 2.9645 | 0.7 |
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- | 0.0013 | 106.0 | 106 | 2.9375 | 0.7 |
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- | 0.0013 | 107.0 | 107 | 2.9101 | 0.7 |
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- | 0.0013 | 108.0 | 108 | 2.8796 | 0.7 |
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- | 0.0013 | 109.0 | 109 | 2.8490 | 0.7 |
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- | 0.004 | 110.0 | 110 | 2.8199 | 0.7 |
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- | 0.004 | 111.0 | 111 | 2.7971 | 0.7 |
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- | 0.004 | 112.0 | 112 | 2.7819 | 0.7 |
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- | 0.004 | 113.0 | 113 | 2.7880 | 0.7 |
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- | 0.004 | 114.0 | 114 | 2.7990 | 0.7 |
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- | 0.004 | 115.0 | 115 | 2.8067 | 0.7 |
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- | 0.004 | 116.0 | 116 | 2.8085 | 0.7 |
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- | 0.004 | 117.0 | 117 | 2.8047 | 0.7 |
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- | 0.004 | 118.0 | 118 | 2.7986 | 0.7 |
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- | 0.004 | 119.0 | 119 | 2.7904 | 0.7 |
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- | 0.0002 | 120.0 | 120 | 2.7798 | 0.7 |
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- | 0.0002 | 121.0 | 121 | 2.7701 | 0.7 |
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- | 0.0002 | 122.0 | 122 | 2.7585 | 0.7 |
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- | 0.0002 | 123.0 | 123 | 2.7011 | 0.7167 |
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- | 0.0002 | 124.0 | 124 | 2.6480 | 0.7333 |
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- | 0.0002 | 125.0 | 125 | 2.7229 | 0.7333 |
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- | 0.0002 | 126.0 | 126 | 2.7787 | 0.7167 |
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- | 0.0002 | 127.0 | 127 | 2.8531 | 0.7167 |
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- | 0.0002 | 128.0 | 128 | 2.9118 | 0.7167 |
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- | 0.0002 | 129.0 | 129 | 2.9455 | 0.7167 |
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- | 0.0062 | 130.0 | 130 | 2.9612 | 0.7167 |
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- | 0.0062 | 131.0 | 131 | 2.9643 | 0.7167 |
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- | 0.0062 | 132.0 | 132 | 2.9574 | 0.7167 |
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- | 0.0062 | 133.0 | 133 | 2.9440 | 0.7167 |
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- | 0.0062 | 134.0 | 134 | 2.9261 | 0.7 |
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- | 0.0062 | 135.0 | 135 | 2.9091 | 0.7 |
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- | 0.0062 | 136.0 | 136 | 2.9030 | 0.7167 |
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- | 0.0062 | 137.0 | 137 | 2.9087 | 0.7167 |
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- | 0.0062 | 138.0 | 138 | 2.9180 | 0.7167 |
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- | 0.0062 | 139.0 | 139 | 2.9304 | 0.7167 |
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- | 0.0001 | 140.0 | 140 | 2.9454 | 0.7 |
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- | 0.0001 | 141.0 | 141 | 2.9443 | 0.7 |
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- | 0.0001 | 142.0 | 142 | 2.9435 | 0.7 |
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- | 0.0001 | 143.0 | 143 | 2.9901 | 0.7 |
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- | 0.0001 | 144.0 | 144 | 3.0264 | 0.7 |
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- | 0.0001 | 145.0 | 145 | 3.0492 | 0.7 |
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- | 0.0001 | 146.0 | 146 | 3.0667 | 0.7 |
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- | 0.0001 | 147.0 | 147 | 3.0946 | 0.6833 |
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- | 0.0001 | 148.0 | 148 | 3.1313 | 0.6833 |
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- | 0.0001 | 149.0 | 149 | 3.1607 | 0.6833 |
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- | 0.0056 | 150.0 | 150 | 3.1847 | 0.6833 |
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- | 0.0056 | 151.0 | 151 | 3.2101 | 0.6667 |
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- | 0.0056 | 152.0 | 152 | 3.2372 | 0.6667 |
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- | 0.0056 | 153.0 | 153 | 3.2586 | 0.6667 |
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- | 0.0056 | 154.0 | 154 | 3.2746 | 0.6667 |
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- | 0.0056 | 155.0 | 155 | 3.2779 | 0.6667 |
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- | 0.0056 | 156.0 | 156 | 3.2765 | 0.6667 |
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- | 0.0056 | 157.0 | 157 | 3.2711 | 0.6667 |
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- | 0.0056 | 158.0 | 158 | 3.2649 | 0.6667 |
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- | 0.0056 | 159.0 | 159 | 3.2585 | 0.6667 |
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- | 0.0003 | 160.0 | 160 | 3.2501 | 0.6667 |
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- | 0.0003 | 161.0 | 161 | 3.2426 | 0.6667 |
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- | 0.0003 | 162.0 | 162 | 3.2357 | 0.6667 |
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- | 0.0003 | 163.0 | 163 | 3.2463 | 0.6667 |
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- | 0.0003 | 164.0 | 164 | 3.2492 | 0.6667 |
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- | 0.0003 | 165.0 | 165 | 3.2475 | 0.6667 |
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- | 0.0003 | 166.0 | 166 | 3.2441 | 0.6667 |
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- | 0.0003 | 167.0 | 167 | 3.2392 | 0.6667 |
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- | 0.0003 | 168.0 | 168 | 3.2336 | 0.6667 |
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- | 0.0003 | 169.0 | 169 | 3.2172 | 0.6833 |
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- | 0.0043 | 170.0 | 170 | 3.2056 | 0.6833 |
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- | 0.0043 | 171.0 | 171 | 3.2055 | 0.6667 |
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- | 0.0043 | 172.0 | 172 | 3.2140 | 0.6667 |
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- | 0.0043 | 173.0 | 173 | 3.1344 | 0.7 |
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- | 0.0043 | 174.0 | 174 | 3.0989 | 0.7 |
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- | 0.0043 | 175.0 | 175 | 3.0715 | 0.7 |
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- | 0.0043 | 176.0 | 176 | 3.0426 | 0.7 |
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- | 0.0043 | 177.0 | 177 | 3.0115 | 0.7 |
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- | 0.0043 | 178.0 | 178 | 2.9716 | 0.7 |
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- | 0.0043 | 179.0 | 179 | 2.9265 | 0.7 |
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- | 0.0081 | 180.0 | 180 | 2.8742 | 0.7167 |
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- | 0.0081 | 181.0 | 181 | 2.8181 | 0.7167 |
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- | 0.0081 | 182.0 | 182 | 2.7616 | 0.7167 |
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- | 0.0081 | 183.0 | 183 | 2.7368 | 0.7 |
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- | 0.0081 | 184.0 | 184 | 2.7249 | 0.7167 |
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- | 0.0081 | 185.0 | 185 | 2.7164 | 0.7167 |
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- | 0.0081 | 186.0 | 186 | 2.7074 | 0.7167 |
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- | 0.0081 | 187.0 | 187 | 2.6971 | 0.7167 |
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- | 0.0081 | 188.0 | 188 | 2.6883 | 0.7167 |
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- | 0.0081 | 189.0 | 189 | 2.6792 | 0.7167 |
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- | 0.0003 | 190.0 | 190 | 2.6679 | 0.7167 |
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- | 0.0003 | 191.0 | 191 | 2.6592 | 0.7167 |
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- | 0.0003 | 192.0 | 192 | 2.6494 | 0.7167 |
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- | 0.0003 | 193.0 | 193 | 2.6436 | 0.7167 |
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- | 0.0003 | 194.0 | 194 | 2.6381 | 0.7167 |
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- | 0.0003 | 195.0 | 195 | 2.6378 | 0.7167 |
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- | 0.0003 | 196.0 | 196 | 2.6364 | 0.7167 |
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- | 0.0003 | 197.0 | 197 | 2.6363 | 0.7167 |
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- | 0.0003 | 198.0 | 198 | 2.6356 | 0.7167 |
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- | 0.0003 | 199.0 | 199 | 2.6352 | 0.7167 |
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- | 0.0024 | 200.0 | 200 | 2.6350 | 0.7167 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 3.0600
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+ - Accuracy: 0.7
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  ## Model description
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46
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 100
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 1 | 2.6350 | 0.7167 |
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+ | No log | 2.0 | 2 | 2.7406 | 0.7167 |
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+ | No log | 3.0 | 3 | 2.8632 | 0.7 |
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+ | No log | 4.0 | 4 | 2.8745 | 0.7 |
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+ | No log | 5.0 | 5 | 2.9112 | 0.7 |
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+ | No log | 6.0 | 6 | 2.9644 | 0.6833 |
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+ | No log | 7.0 | 7 | 3.3638 | 0.65 |
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+ | No log | 8.0 | 8 | 3.8127 | 0.5833 |
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+ | No log | 9.0 | 9 | 4.2359 | 0.5833 |
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+ | 0.0038 | 10.0 | 10 | 3.7159 | 0.6167 |
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+ | 0.0038 | 11.0 | 11 | 3.2066 | 0.65 |
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+ | 0.0038 | 12.0 | 12 | 2.9436 | 0.7333 |
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+ | 0.0038 | 13.0 | 13 | 3.1083 | 0.7 |
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+ | 0.0038 | 14.0 | 14 | 3.4327 | 0.6833 |
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+ | 0.0038 | 15.0 | 15 | 3.4017 | 0.6833 |
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+ | 0.0038 | 16.0 | 16 | 3.1088 | 0.7 |
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+ | 0.0038 | 17.0 | 17 | 2.9279 | 0.7 |
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+ | 0.0038 | 18.0 | 18 | 2.9036 | 0.7333 |
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+ | 0.0038 | 19.0 | 19 | 2.9245 | 0.7167 |
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+ | 0.0097 | 20.0 | 20 | 2.8291 | 0.7333 |
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+ | 0.0097 | 21.0 | 21 | 2.8655 | 0.7 |
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+ | 0.0097 | 22.0 | 22 | 2.7505 | 0.7167 |
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+ | 0.0097 | 23.0 | 23 | 2.6406 | 0.7333 |
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+ | 0.0097 | 24.0 | 24 | 2.6017 | 0.7333 |
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+ | 0.0097 | 25.0 | 25 | 2.5550 | 0.75 |
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+ | 0.0097 | 26.0 | 26 | 2.5972 | 0.75 |
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+ | 0.0097 | 27.0 | 27 | 2.6193 | 0.7333 |
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+ | 0.0097 | 28.0 | 28 | 2.6949 | 0.7167 |
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+ | 0.0097 | 29.0 | 29 | 2.8405 | 0.6833 |
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+ | 0.0052 | 30.0 | 30 | 2.8552 | 0.7 |
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+ | 0.0052 | 31.0 | 31 | 2.7041 | 0.7 |
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+ | 0.0052 | 32.0 | 32 | 2.5161 | 0.7333 |
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+ | 0.0052 | 33.0 | 33 | 2.4609 | 0.7333 |
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+ | 0.0052 | 34.0 | 34 | 2.4119 | 0.7333 |
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+ | 0.0052 | 35.0 | 35 | 2.3811 | 0.75 |
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+ | 0.0052 | 36.0 | 36 | 2.4323 | 0.75 |
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+ | 0.0052 | 37.0 | 37 | 2.6068 | 0.75 |
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+ | 0.0052 | 38.0 | 38 | 2.6425 | 0.75 |
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+ | 0.0052 | 39.0 | 39 | 2.6534 | 0.75 |
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+ | 0.004 | 40.0 | 40 | 2.6643 | 0.7333 |
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+ | 0.004 | 41.0 | 41 | 2.6912 | 0.7167 |
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+ | 0.004 | 42.0 | 42 | 2.7284 | 0.7 |
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+ | 0.004 | 43.0 | 43 | 2.7621 | 0.7 |
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+ | 0.004 | 44.0 | 44 | 2.7870 | 0.7 |
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+ | 0.004 | 45.0 | 45 | 2.8085 | 0.7 |
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+ | 0.004 | 46.0 | 46 | 2.8251 | 0.7 |
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+ | 0.004 | 47.0 | 47 | 2.8478 | 0.7167 |
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+ | 0.004 | 48.0 | 48 | 2.8729 | 0.7 |
103
+ | 0.004 | 49.0 | 49 | 2.8999 | 0.7 |
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+ | 0.0001 | 50.0 | 50 | 2.9256 | 0.7 |
105
+ | 0.0001 | 51.0 | 51 | 2.9287 | 0.7 |
106
+ | 0.0001 | 52.0 | 52 | 2.8962 | 0.7 |
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+ | 0.0001 | 53.0 | 53 | 2.8783 | 0.6833 |
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+ | 0.0001 | 54.0 | 54 | 2.8959 | 0.7167 |
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+ | 0.0001 | 55.0 | 55 | 2.8606 | 0.7167 |
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+ | 0.0001 | 56.0 | 56 | 2.7337 | 0.7167 |
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+ | 0.0001 | 57.0 | 57 | 2.7450 | 0.7 |
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+ | 0.0001 | 58.0 | 58 | 2.9678 | 0.6667 |
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+ | 0.0001 | 59.0 | 59 | 3.1560 | 0.6667 |
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+ | 0.0145 | 60.0 | 60 | 3.4292 | 0.6333 |
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+ | 0.0145 | 61.0 | 61 | 3.5474 | 0.6167 |
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+ | 0.0145 | 62.0 | 62 | 3.6343 | 0.6167 |
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+ | 0.0145 | 63.0 | 63 | 3.5805 | 0.6167 |
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+ | 0.0145 | 64.0 | 64 | 3.5623 | 0.6333 |
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+ | 0.0145 | 65.0 | 65 | 3.5532 | 0.6333 |
120
+ | 0.0145 | 66.0 | 66 | 3.6041 | 0.6 |
121
+ | 0.0145 | 67.0 | 67 | 3.7335 | 0.6 |
122
+ | 0.0145 | 68.0 | 68 | 3.8447 | 0.6 |
123
+ | 0.0145 | 69.0 | 69 | 3.8997 | 0.6167 |
124
+ | 0.0001 | 70.0 | 70 | 3.8381 | 0.6167 |
125
+ | 0.0001 | 71.0 | 71 | 3.7951 | 0.6 |
126
+ | 0.0001 | 72.0 | 72 | 3.8582 | 0.6 |
127
+ | 0.0001 | 73.0 | 73 | 3.8983 | 0.6 |
128
+ | 0.0001 | 74.0 | 74 | 3.8225 | 0.6167 |
129
+ | 0.0001 | 75.0 | 75 | 3.6746 | 0.65 |
130
+ | 0.0001 | 76.0 | 76 | 3.5636 | 0.65 |
131
+ | 0.0001 | 77.0 | 77 | 3.5198 | 0.6667 |
132
+ | 0.0001 | 78.0 | 78 | 3.4888 | 0.6667 |
133
+ | 0.0001 | 79.0 | 79 | 3.4752 | 0.65 |
134
+ | 0.004 | 80.0 | 80 | 3.4661 | 0.65 |
135
+ | 0.004 | 81.0 | 81 | 3.4177 | 0.65 |
136
+ | 0.004 | 82.0 | 82 | 3.3299 | 0.65 |
137
+ | 0.004 | 83.0 | 83 | 3.2658 | 0.6667 |
138
+ | 0.004 | 84.0 | 84 | 3.2386 | 0.6833 |
139
+ | 0.004 | 85.0 | 85 | 3.2177 | 0.7 |
140
+ | 0.004 | 86.0 | 86 | 3.1985 | 0.7 |
141
+ | 0.004 | 87.0 | 87 | 3.1800 | 0.7 |
142
+ | 0.004 | 88.0 | 88 | 3.1624 | 0.7 |
143
+ | 0.004 | 89.0 | 89 | 3.1451 | 0.7 |
144
+ | 0.0001 | 90.0 | 90 | 3.1292 | 0.7 |
145
+ | 0.0001 | 91.0 | 91 | 3.1145 | 0.7 |
146
+ | 0.0001 | 92.0 | 92 | 3.1022 | 0.7 |
147
+ | 0.0001 | 93.0 | 93 | 3.0917 | 0.7 |
148
+ | 0.0001 | 94.0 | 94 | 3.0817 | 0.7 |
149
+ | 0.0001 | 95.0 | 95 | 3.0753 | 0.7 |
150
+ | 0.0001 | 96.0 | 96 | 3.0691 | 0.7 |
151
+ | 0.0001 | 97.0 | 97 | 3.0658 | 0.7 |
152
+ | 0.0001 | 98.0 | 98 | 3.0623 | 0.7 |
153
+ | 0.0001 | 99.0 | 99 | 3.0608 | 0.7 |
154
+ | 0.0 | 100.0 | 100 | 3.0600 | 0.7 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
155
 
156
 
157
  ### Framework versions