Hugging Face's logo

fydhfzh
/
hubert-classifier

Audio Classification
Transformers
TensorBoard
Safetensors
hubert
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
fydhfzh commited on
Commit
7ce2631
•
1 Parent(s): 991aa7a

End of training

Browse files
Files changed (2) hide show
  1. README.md +17 -63
  2. runs/Jun17_15-21-17_LAPTOP-1GID9RGH/events.out.tfevents.1718612478.LAPTOP-1GID9RGH.11192.0 +2 -2
README.md CHANGED
@@ -20,12 +20,12 @@ should probably proofread and complete it, then remove this comment. -->
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: 1.1058
24
- - Accuracy: 0.7748
25
- - Precision: 0.8018
26
- - Recall: 0.7748
27
- - F1: 0.7651
28
- - Binary: 0.8455
29
 
30
  ## Model description
31
 
@@ -59,63 +59,17 @@ The following hyperparameters were used during training:
59
 
60
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Binary |
61
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
62
- | No log | 0.17 | 50 | 4.2665 | 0.0412 | 0.0107 | 0.0412 | 0.0127 | 0.2923 |
63
- | No log | 0.35 | 100 | 3.9427 | 0.0339 | 0.0016 | 0.0339 | 0.0030 | 0.3172 |
64
- | No log | 0.52 | 150 | 3.7412 | 0.0363 | 0.0025 | 0.0363 | 0.0041 | 0.3206 |
65
- | No log | 0.69 | 200 | 3.6193 | 0.0654 | 0.0238 | 0.0654 | 0.0259 | 0.3373 |
66
- | No log | 0.86 | 250 | 3.4784 | 0.1041 | 0.0460 | 0.1041 | 0.0459 | 0.3663 |
67
- | No log | 1.04 | 300 | 3.3705 | 0.1211 | 0.0602 | 0.1211 | 0.0466 | 0.3789 |
68
- | No log | 1.21 | 350 | 3.2597 | 0.1768 | 0.0811 | 0.1768 | 0.0894 | 0.4218 |
69
- | No log | 1.38 | 400 | 3.1606 | 0.2082 | 0.1867 | 0.2082 | 0.1416 | 0.4424 |
70
- | No log | 1.55 | 450 | 3.0720 | 0.1913 | 0.1490 | 0.1913 | 0.1296 | 0.4312 |
71
- | 3.6525 | 1.73 | 500 | 2.9557 | 0.2446 | 0.1432 | 0.2446 | 0.1609 | 0.4671 |
72
- | 3.6525 | 1.9 | 550 | 2.8287 | 0.2857 | 0.2265 | 0.2857 | 0.2059 | 0.4973 |
73
- | 3.6525 | 2.07 | 600 | 2.7005 | 0.3075 | 0.2103 | 0.3075 | 0.2154 | 0.5136 |
74
- | 3.6525 | 2.24 | 650 | 2.6183 | 0.3414 | 0.2398 | 0.3414 | 0.2486 | 0.5341 |
75
- | 3.6525 | 2.42 | 700 | 2.5133 | 0.3632 | 0.2942 | 0.3632 | 0.2732 | 0.5516 |
76
- | 3.6525 | 2.59 | 750 | 2.4277 | 0.3753 | 0.3322 | 0.3753 | 0.2948 | 0.5615 |
77
- | 3.6525 | 2.76 | 800 | 2.3329 | 0.4092 | 0.3538 | 0.4092 | 0.3338 | 0.5845 |
78
- | 3.6525 | 2.93 | 850 | 2.2465 | 0.4407 | 0.4125 | 0.4407 | 0.3745 | 0.6073 |
79
- | 3.6525 | 3.11 | 900 | 2.1792 | 0.4600 | 0.4329 | 0.4600 | 0.3995 | 0.6203 |
80
- | 3.6525 | 3.28 | 950 | 2.1004 | 0.5109 | 0.4995 | 0.5109 | 0.4540 | 0.6550 |
81
- | 2.6844 | 3.45 | 1000 | 2.0314 | 0.5109 | 0.4799 | 0.5109 | 0.4520 | 0.6557 |
82
- | 2.6844 | 3.62 | 1050 | 1.9561 | 0.5400 | 0.5309 | 0.5400 | 0.4859 | 0.6743 |
83
- | 2.6844 | 3.8 | 1100 | 1.9362 | 0.5472 | 0.5441 | 0.5472 | 0.5066 | 0.6804 |
84
- | 2.6844 | 3.97 | 1150 | 1.8666 | 0.5642 | 0.5647 | 0.5642 | 0.5232 | 0.6930 |
85
- | 2.6844 | 4.14 | 1200 | 1.8204 | 0.5811 | 0.5716 | 0.5811 | 0.5416 | 0.7048 |
86
- | 2.6844 | 4.31 | 1250 | 1.7494 | 0.5908 | 0.6153 | 0.5908 | 0.5618 | 0.7109 |
87
- | 2.6844 | 4.49 | 1300 | 1.6973 | 0.6126 | 0.6062 | 0.6126 | 0.5804 | 0.7291 |
88
- | 2.6844 | 4.66 | 1350 | 1.6615 | 0.6053 | 0.5864 | 0.6053 | 0.5707 | 0.7211 |
89
- | 2.6844 | 4.83 | 1400 | 1.6120 | 0.6295 | 0.6304 | 0.6295 | 0.6000 | 0.7385 |
90
- | 2.6844 | 5.0 | 1450 | 1.5620 | 0.6610 | 0.6605 | 0.6610 | 0.6333 | 0.7615 |
91
- | 2.1096 | 5.18 | 1500 | 1.5330 | 0.6538 | 0.6424 | 0.6538 | 0.6223 | 0.7581 |
92
- | 2.1096 | 5.35 | 1550 | 1.5112 | 0.6707 | 0.6830 | 0.6707 | 0.6484 | 0.7707 |
93
- | 2.1096 | 5.52 | 1600 | 1.4732 | 0.6659 | 0.6793 | 0.6659 | 0.6430 | 0.7685 |
94
- | 2.1096 | 5.69 | 1650 | 1.4420 | 0.6755 | 0.6969 | 0.6755 | 0.6538 | 0.7734 |
95
- | 2.1096 | 5.87 | 1700 | 1.4011 | 0.7094 | 0.7461 | 0.7094 | 0.6929 | 0.7988 |
96
- | 2.1096 | 6.04 | 1750 | 1.3924 | 0.6780 | 0.6835 | 0.6780 | 0.6557 | 0.7760 |
97
- | 2.1096 | 6.21 | 1800 | 1.3604 | 0.7022 | 0.7116 | 0.7022 | 0.6838 | 0.7937 |
98
- | 2.1096 | 6.38 | 1850 | 1.3271 | 0.7070 | 0.7079 | 0.7070 | 0.6882 | 0.7954 |
99
- | 2.1096 | 6.56 | 1900 | 1.3104 | 0.7264 | 0.7338 | 0.7264 | 0.7110 | 0.8099 |
100
- | 2.1096 | 6.73 | 1950 | 1.2804 | 0.7312 | 0.7591 | 0.7312 | 0.7159 | 0.8131 |
101
- | 1.7648 | 6.9 | 2000 | 1.2722 | 0.7312 | 0.7739 | 0.7312 | 0.7185 | 0.8131 |
102
- | 1.7648 | 7.08 | 2050 | 1.2777 | 0.7240 | 0.7581 | 0.7240 | 0.7109 | 0.8099 |
103
- | 1.7648 | 7.25 | 2100 | 1.2319 | 0.7288 | 0.7373 | 0.7288 | 0.7114 | 0.8123 |
104
- | 1.7648 | 7.42 | 2150 | 1.2074 | 0.7433 | 0.7717 | 0.7433 | 0.7317 | 0.8215 |
105
- | 1.7648 | 7.59 | 2200 | 1.2150 | 0.7433 | 0.7850 | 0.7433 | 0.7348 | 0.8235 |
106
- | 1.7648 | 7.77 | 2250 | 1.1787 | 0.7603 | 0.7930 | 0.7603 | 0.7462 | 0.8344 |
107
- | 1.7648 | 7.94 | 2300 | 1.1815 | 0.7676 | 0.7932 | 0.7676 | 0.7576 | 0.8404 |
108
- | 1.7648 | 8.11 | 2350 | 1.1578 | 0.7676 | 0.7972 | 0.7676 | 0.7601 | 0.8404 |
109
- | 1.7648 | 8.28 | 2400 | 1.1605 | 0.7651 | 0.7982 | 0.7651 | 0.7560 | 0.8387 |
110
- | 1.7648 | 8.46 | 2450 | 1.1563 | 0.7627 | 0.7937 | 0.7627 | 0.7548 | 0.8370 |
111
- | 1.5781 | 8.63 | 2500 | 1.1303 | 0.7579 | 0.7847 | 0.7579 | 0.7476 | 0.8337 |
112
- | 1.5781 | 8.8 | 2550 | 1.1217 | 0.7797 | 0.8117 | 0.7797 | 0.7702 | 0.8489 |
113
- | 1.5781 | 8.97 | 2600 | 1.1278 | 0.7724 | 0.8025 | 0.7724 | 0.7640 | 0.8438 |
114
- | 1.5781 | 9.15 | 2650 | 1.1188 | 0.7748 | 0.8022 | 0.7748 | 0.7653 | 0.8455 |
115
- | 1.5781 | 9.32 | 2700 | 1.1161 | 0.7676 | 0.7979 | 0.7676 | 0.7588 | 0.8404 |
116
- | 1.5781 | 9.49 | 2750 | 1.1078 | 0.7748 | 0.8012 | 0.7748 | 0.7650 | 0.8446 |
117
- | 1.5781 | 9.66 | 2800 | 1.1104 | 0.7724 | 0.7973 | 0.7724 | 0.7632 | 0.8429 |
118
- | 1.5781 | 9.84 | 2850 | 1.1058 | 0.7748 | 0.8018 | 0.7748 | 0.7651 | 0.8455 |
119
 
120
 
121
  ### Framework versions
 
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: 3.4231
24
+ - Accuracy: 0.0993
25
+ - Precision: 0.0191
26
+ - Recall: 0.0993
27
+ - F1: 0.0296
28
+ - Binary: 0.3603
29
 
30
  ## Model description
31
 
 
59
 
60
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Binary |
61
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
62
+ | No log | 0.86 | 50 | 4.4031 | 0.0218 | 0.0042 | 0.0218 | 0.0061 | 0.1886 |
63
+ | No log | 1.72 | 100 | 4.1752 | 0.0363 | 0.0204 | 0.0363 | 0.0100 | 0.3102 |
64
+ | No log | 2.59 | 150 | 3.9334 | 0.0363 | 0.0159 | 0.0363 | 0.0125 | 0.3102 |
65
+ | No log | 3.45 | 200 | 3.7751 | 0.0557 | 0.0270 | 0.0557 | 0.0268 | 0.3266 |
66
+ | No log | 4.31 | 250 | 3.6877 | 0.0775 | 0.0241 | 0.0775 | 0.0314 | 0.3383 |
67
+ | No log | 5.17 | 300 | 3.5839 | 0.0920 | 0.0220 | 0.0920 | 0.0329 | 0.3550 |
68
+ | No log | 6.03 | 350 | 3.5119 | 0.0920 | 0.0219 | 0.0920 | 0.0327 | 0.3586 |
69
+ | No log | 6.9 | 400 | 3.4851 | 0.0872 | 0.0274 | 0.0872 | 0.0283 | 0.3508 |
70
+ | No log | 7.76 | 450 | 3.4593 | 0.0920 | 0.0221 | 0.0920 | 0.0312 | 0.3552 |
71
+ | 3.8751 | 8.62 | 500 | 3.4240 | 0.1017 | 0.0223 | 0.1017 | 0.0328 | 0.3610 |
72
+ | 3.8751 | 9.48 | 550 | 3.4231 | 0.0993 | 0.0191 | 0.0993 | 0.0296 | 0.3603 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
73
 
74
 
75
  ### Framework versions
runs/Jun17_15-21-17_LAPTOP-1GID9RGH/events.out.tfevents.1718612478.LAPTOP-1GID9RGH.11192.0 CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:6c48ff10b6402be188c4125ade5499f1f7e6ded85c5d3a3778371abef5fd2fad
3
- size 14433
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d68a2695c93303ecd77f4494a0595542f0cdd52e8c67a810c8fec9dc4cfb5578
3
+ size 15309