Hugging Face's logo

Nugrahasetyaardi
/
SER_model_xapiens

Audio Classification
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
Nugrahasetyaardi commited on
Commit
cb9cb5e
•
1 Parent(s): 57af990

Model save

Browse files
Files changed (1) hide show
  1. README.md +71 -104
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
17
 
18
  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
19
  It achieves the following results on the evaluation set:
20
- - Loss: 2.5738
21
- - Accuracy: 0.3041
22
 
23
  ## Model description
24
 
@@ -50,108 +50,75 @@ The following hyperparameters were used during training:
50
 
51
  ### Training results
52
 
53
- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
54
- |:-------------:|:-----:|:----:|:---------------:|:--------:|
55
- | No log | 1.0 | 9 | 1.7645 | 0.4076 |
56
- | 1.7866 | 2.0 | 18 | 1.7565 | 0.4076 |
57
- | 1.7798 | 3.0 | 27 | 1.7455 | 0.4076 |
58
- | 1.7644 | 4.0 | 36 | 1.7316 | 0.4076 |
59
- | 1.7493 | 5.0 | 45 | 1.7171 | 0.4181 |
60
- | 1.7117 | 6.0 | 54 | 1.7175 | 0.4233 |
61
- | 1.7218 | 7.0 | 63 | 1.7061 | 0.4220 |
62
- | 1.6752 | 8.0 | 72 | 1.7257 | 0.3958 |
63
- | 1.6892 | 9.0 | 81 | 1.7137 | 0.4181 |
64
- | 1.6567 | 10.0 | 90 | 1.7058 | 0.4220 |
65
- | 1.6567 | 11.0 | 99 | 1.7144 | 0.4299 |
66
- | 1.6334 | 12.0 | 108 | 1.7087 | 0.4076 |
67
- | 1.6437 | 13.0 | 117 | 1.7158 | 0.4273 |
68
- | 1.6167 | 14.0 | 126 | 1.7296 | 0.4076 |
69
- | 1.5712 | 15.0 | 135 | 1.7449 | 0.4168 |
70
- | 1.5781 | 16.0 | 144 | 1.7459 | 0.4246 |
71
- | 1.5872 | 17.0 | 153 | 1.7217 | 0.4168 |
72
- | 1.5484 | 18.0 | 162 | 1.7471 | 0.4128 |
73
- | 1.4936 | 19.0 | 171 | 1.7770 | 0.3893 |
74
- | 1.4869 | 20.0 | 180 | 1.7677 | 0.4076 |
75
- | 1.4869 | 21.0 | 189 | 1.8222 | 0.3709 |
76
- | 1.4602 | 22.0 | 198 | 1.7785 | 0.4024 |
77
- | 1.4563 | 23.0 | 207 | 1.8191 | 0.4024 |
78
- | 1.3762 | 24.0 | 216 | 1.7934 | 0.4115 |
79
- | 1.3903 | 25.0 | 225 | 1.8111 | 0.3919 |
80
- | 1.3899 | 26.0 | 234 | 1.9607 | 0.3185 |
81
- | 1.3592 | 27.0 | 243 | 1.8800 | 0.3775 |
82
- | 1.3378 | 28.0 | 252 | 1.8500 | 0.4063 |
83
- | 1.3135 | 29.0 | 261 | 1.8792 | 0.3840 |
84
- | 1.2669 | 30.0 | 270 | 1.9259 | 0.3735 |
85
- | 1.2669 | 31.0 | 279 | 2.0078 | 0.3224 |
86
- | 1.2779 | 32.0 | 288 | 1.9653 | 0.3421 |
87
- | 1.2368 | 33.0 | 297 | 1.9823 | 0.3499 |
88
- | 1.2116 | 34.0 | 306 | 1.9602 | 0.3775 |
89
- | 1.1851 | 35.0 | 315 | 2.0362 | 0.3447 |
90
- | 1.1703 | 36.0 | 324 | 2.0193 | 0.3434 |
91
- | 1.1224 | 37.0 | 333 | 2.0363 | 0.3552 |
92
- | 1.1211 | 38.0 | 342 | 2.0817 | 0.3277 |
93
- | 1.0862 | 39.0 | 351 | 2.0775 | 0.3355 |
94
- | 1.0847 | 40.0 | 360 | 2.1078 | 0.3303 |
95
- | 1.0847 | 41.0 | 369 | 2.1608 | 0.3067 |
96
- | 1.0448 | 42.0 | 378 | 2.0996 | 0.3591 |
97
- | 1.0356 | 43.0 | 387 | 2.1416 | 0.3329 |
98
- | 1.008 | 44.0 | 396 | 2.1892 | 0.3250 |
99
- | 1.0018 | 45.0 | 405 | 2.1390 | 0.3408 |
100
- | 0.9606 | 46.0 | 414 | 2.2137 | 0.3250 |
101
- | 0.9489 | 47.0 | 423 | 2.1843 | 0.3329 |
102
- | 0.9404 | 48.0 | 432 | 2.2826 | 0.2988 |
103
- | 0.9483 | 49.0 | 441 | 2.2073 | 0.3355 |
104
- | 0.9101 | 50.0 | 450 | 2.1827 | 0.3565 |
105
- | 0.9101 | 51.0 | 459 | 2.2765 | 0.3185 |
106
- | 0.896 | 52.0 | 468 | 2.2909 | 0.3080 |
107
- | 0.8558 | 53.0 | 477 | 2.2816 | 0.3014 |
108
- | 0.8433 | 54.0 | 486 | 2.2215 | 0.3342 |
109
- | 0.8194 | 55.0 | 495 | 2.2022 | 0.3565 |
110
- | 0.8436 | 56.0 | 504 | 2.2139 | 0.3630 |
111
- | 0.7808 | 57.0 | 513 | 2.2970 | 0.3054 |
112
- | 0.8009 | 58.0 | 522 | 2.3081 | 0.3329 |
113
- | 0.7575 | 59.0 | 531 | 2.3105 | 0.3119 |
114
- | 0.7894 | 60.0 | 540 | 2.3786 | 0.3028 |
115
- | 0.7894 | 61.0 | 549 | 2.3072 | 0.3185 |
116
- | 0.7532 | 62.0 | 558 | 2.3318 | 0.3014 |
117
- | 0.7222 | 63.0 | 567 | 2.3697 | 0.3172 |
118
- | 0.7116 | 64.0 | 576 | 2.4125 | 0.3198 |
119
- | 0.7286 | 65.0 | 585 | 2.3694 | 0.3119 |
120
- | 0.6906 | 66.0 | 594 | 2.3974 | 0.3028 |
121
- | 0.6642 | 67.0 | 603 | 2.4020 | 0.3001 |
122
- | 0.6737 | 68.0 | 612 | 2.3513 | 0.3316 |
123
- | 0.6571 | 69.0 | 621 | 2.3638 | 0.3447 |
124
- | 0.6482 | 70.0 | 630 | 2.4507 | 0.3014 |
125
- | 0.6482 | 71.0 | 639 | 2.4796 | 0.2831 |
126
- | 0.6407 | 72.0 | 648 | 2.4475 | 0.3119 |
127
- | 0.6198 | 73.0 | 657 | 2.5029 | 0.2883 |
128
- | 0.6087 | 74.0 | 666 | 2.4490 | 0.3119 |
129
- | 0.6074 | 75.0 | 675 | 2.4068 | 0.3316 |
130
- | 0.5941 | 76.0 | 684 | 2.4878 | 0.3106 |
131
- | 0.5922 | 77.0 | 693 | 2.5032 | 0.2988 |
132
- | 0.6028 | 78.0 | 702 | 2.4904 | 0.3054 |
133
- | 0.5867 | 79.0 | 711 | 2.4592 | 0.3224 |
134
- | 0.5677 | 80.0 | 720 | 2.5277 | 0.2936 |
135
- | 0.5677 | 81.0 | 729 | 2.4852 | 0.3211 |
136
- | 0.5459 | 82.0 | 738 | 2.5210 | 0.3014 |
137
- | 0.5346 | 83.0 | 747 | 2.5432 | 0.3001 |
138
- | 0.5572 | 84.0 | 756 | 2.4974 | 0.3172 |
139
- | 0.5246 | 85.0 | 765 | 2.5649 | 0.3001 |
140
- | 0.5163 | 86.0 | 774 | 2.5256 | 0.3198 |
141
- | 0.5231 | 87.0 | 783 | 2.5010 | 0.3224 |
142
- | 0.5141 | 88.0 | 792 | 2.5648 | 0.2975 |
143
- | 0.5014 | 89.0 | 801 | 2.5405 | 0.3080 |
144
- | 0.5125 | 90.0 | 810 | 2.5851 | 0.2988 |
145
- | 0.5125 | 91.0 | 819 | 2.5525 | 0.3001 |
146
- | 0.4922 | 92.0 | 828 | 2.5313 | 0.3263 |
147
- | 0.5109 | 93.0 | 837 | 2.5660 | 0.3028 |
148
- | 0.4847 | 94.0 | 846 | 2.5406 | 0.3132 |
149
- | 0.4702 | 95.0 | 855 | 2.5681 | 0.3028 |
150
- | 0.4929 | 96.0 | 864 | 2.5796 | 0.2988 |
151
- | 0.4653 | 97.0 | 873 | 2.5813 | 0.2962 |
152
- | 0.4866 | 98.0 | 882 | 2.5720 | 0.3028 |
153
- | 0.4591 | 99.0 | 891 | 2.5717 | 0.3054 |
154
- | 0.4891 | 100.0 | 900 | 2.5738 | 0.3041 |
155
 
156
 
157
  ### Framework versions
 
17
 
18
  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
19
  It achieves the following results on the evaluation set:
20
+ - Loss: 0.9329
21
+ - Accuracy: 0.6667
22
 
23
  ## Model description
24
 
 
50
 
51
  ### Training results
52
 
53
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
54
+ |:-------------:|:-------:|:----:|:---------------:|:--------:|
55
+ | No log | 1.0 | 1 | 1.6121 | 0.2167 |
56
+ | No log | 2.0 | 3 | 1.6109 | 0.2333 |
57
+ | No log | 3.0 | 5 | 1.6090 | 0.25 |
58
+ | No log | 4.0 | 6 | 1.6078 | 0.2667 |
59
+ | No log | 5.0 | 7 | 1.6058 | 0.2833 |
60
+ | No log | 6.0 | 9 | 1.6006 | 0.35 |
61
+ | 0.8024 | 7.0 | 11 | 1.5947 | 0.35 |
62
+ | 0.8024 | 8.0 | 12 | 1.5894 | 0.3667 |
63
+ | 0.8024 | 9.0 | 13 | 1.5809 | 0.35 |
64
+ | 0.8024 | 10.0 | 15 | 1.5609 | 0.3667 |
65
+ | 0.8024 | 11.0 | 17 | 1.5417 | 0.4 |
66
+ | 0.8024 | 12.0 | 18 | 1.5310 | 0.4167 |
67
+ | 0.8024 | 13.0 | 19 | 1.5147 | 0.4333 |
68
+ | 0.7692 | 14.0 | 21 | 1.4847 | 0.4833 |
69
+ | 0.7692 | 15.0 | 23 | 1.4592 | 0.5167 |
70
+ | 0.7692 | 16.0 | 24 | 1.4384 | 0.5 |
71
+ | 0.7692 | 17.0 | 25 | 1.4147 | 0.5 |
72
+ | 0.7692 | 18.0 | 27 | 1.3769 | 0.5167 |
73
+ | 0.7692 | 19.0 | 29 | 1.3544 | 0.5167 |
74
+ | 0.6858 | 20.0 | 30 | 1.3325 | 0.55 |
75
+ | 0.6858 | 21.0 | 31 | 1.3084 | 0.55 |
76
+ | 0.6858 | 22.0 | 33 | 1.2617 | 0.5667 |
77
+ | 0.6858 | 23.0 | 35 | 1.2359 | 0.6 |
78
+ | 0.6858 | 24.0 | 36 | 1.2245 | 0.5833 |
79
+ | 0.6858 | 25.0 | 37 | 1.2005 | 0.6333 |
80
+ | 0.6858 | 26.0 | 39 | 1.1695 | 0.6333 |
81
+ | 0.5744 | 27.0 | 41 | 1.1539 | 0.6 |
82
+ | 0.5744 | 28.0 | 42 | 1.1370 | 0.6333 |
83
+ | 0.5744 | 29.0 | 43 | 1.1075 | 0.65 |
84
+ | 0.5744 | 30.0 | 45 | 1.0617 | 0.6833 |
85
+ | 0.5744 | 31.0 | 47 | 1.0745 | 0.6167 |
86
+ | 0.5744 | 32.0 | 48 | 1.0653 | 0.5833 |
87
+ | 0.5744 | 33.0 | 49 | 1.0667 | 0.5833 |
88
+ | 0.4853 | 34.0 | 51 | 1.0611 | 0.6 |
89
+ | 0.4853 | 35.0 | 53 | 1.1032 | 0.6333 |
90
+ | 0.4853 | 36.0 | 54 | 1.0963 | 0.6167 |
91
+ | 0.4853 | 37.0 | 55 | 1.0748 | 0.6167 |
92
+ | 0.4853 | 38.0 | 57 | 1.0446 | 0.6333 |
93
+ | 0.4853 | 39.0 | 59 | 1.0205 | 0.6167 |
94
+ | 0.4276 | 40.0 | 60 | 1.0241 | 0.6333 |
95
+ | 0.4276 | 41.0 | 61 | 1.0499 | 0.6167 |
96
+ | 0.4276 | 42.0 | 63 | 1.0788 | 0.6167 |
97
+ | 0.4276 | 43.0 | 65 | 1.0358 | 0.6167 |
98
+ | 0.4276 | 44.0 | 66 | 1.0175 | 0.6 |
99
+ | 0.4276 | 45.0 | 67 | 1.0082 | 0.65 |
100
+ | 0.4276 | 46.0 | 69 | 0.9862 | 0.65 |
101
+ | 0.393 | 47.0 | 71 | 0.9763 | 0.6 |
102
+ | 0.393 | 48.0 | 72 | 0.9660 | 0.6 |
103
+ | 0.393 | 49.0 | 73 | 0.9506 | 0.6167 |
104
+ | 0.393 | 50.0 | 75 | 0.9394 | 0.65 |
105
+ | 0.393 | 51.0 | 77 | 0.9393 | 0.7 |
106
+ | 0.393 | 52.0 | 78 | 0.9463 | 0.65 |
107
+ | 0.393 | 53.0 | 79 | 0.9643 | 0.6167 |
108
+ | 0.3588 | 54.0 | 81 | 0.9750 | 0.6333 |
109
+ | 0.3588 | 55.0 | 83 | 0.9558 | 0.65 |
110
+ | 0.3588 | 56.0 | 84 | 0.9494 | 0.6333 |
111
+ | 0.3588 | 57.0 | 85 | 0.9450 | 0.6167 |
112
+ | 0.3588 | 58.0 | 87 | 0.9466 | 0.6 |
113
+ | 0.3588 | 59.0 | 89 | 0.9385 | 0.6 |
114
+ | 0.3372 | 60.0 | 90 | 0.9343 | 0.6667 |
115
+ | 0.3372 | 61.0 | 91 | 0.9309 | 0.6667 |
116
+ | 0.3372 | 62.0 | 93 | 0.9286 | 0.65 |
117
+ | 0.3372 | 63.0 | 95 | 0.9301 | 0.65 |
118
+ | 0.3372 | 64.0 | 96 | 0.9313 | 0.65 |
119
+ | 0.3372 | 65.0 | 97 | 0.9314 | 0.6667 |
120
+ | 0.3372 | 66.0 | 99 | 0.9327 | 0.6667 |
121
+ | 0.3246 | 66.6667 | 100 | 0.9329 | 0.6667 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
122
 
123
 
124
  ### Framework versions