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
7f768a6
•
1 Parent(s): 1a066b6

Model save

Browse files
Files changed (1) hide show
  1. README.md +104 -71
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: 0.8673
21
- - Accuracy: 0.7
22
 
23
  ## Model description
24
 
@@ -50,75 +50,108 @@ 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 | 1 | 0.9329 | 0.6667 |
56
- | No log | 2.0 | 3 | 0.9100 | 0.7167 |
57
- | No log | 3.0 | 5 | 0.9221 | 0.7333 |
58
- | No log | 4.0 | 6 | 0.9121 | 0.7333 |
59
- | No log | 5.0 | 7 | 0.9391 | 0.6833 |
60
- | No log | 6.0 | 9 | 0.9593 | 0.6667 |
61
- | 0.3147 | 7.0 | 11 | 0.9780 | 0.65 |
62
- | 0.3147 | 8.0 | 12 | 0.9659 | 0.6667 |
63
- | 0.3147 | 9.0 | 13 | 0.9612 | 0.6833 |
64
- | 0.3147 | 10.0 | 15 | 0.9492 | 0.7333 |
65
- | 0.3147 | 11.0 | 17 | 0.9959 | 0.6667 |
66
- | 0.3147 | 12.0 | 18 | 0.9615 | 0.6167 |
67
- | 0.3147 | 13.0 | 19 | 0.9160 | 0.65 |
68
- | 0.2707 | 14.0 | 21 | 0.9024 | 0.6833 |
69
- | 0.2707 | 15.0 | 23 | 0.9288 | 0.6667 |
70
- | 0.2707 | 16.0 | 24 | 0.8897 | 0.7 |
71
- | 0.2707 | 17.0 | 25 | 0.9008 | 0.6833 |
72
- | 0.2707 | 18.0 | 27 | 0.9367 | 0.6833 |
73
- | 0.2707 | 19.0 | 29 | 0.8923 | 0.7667 |
74
- | 0.2198 | 20.0 | 30 | 0.8834 | 0.7833 |
75
- | 0.2198 | 21.0 | 31 | 0.8932 | 0.7667 |
76
- | 0.2198 | 22.0 | 33 | 0.8992 | 0.7167 |
77
- | 0.2198 | 23.0 | 35 | 0.9127 | 0.7 |
78
- | 0.2198 | 24.0 | 36 | 0.9262 | 0.6667 |
79
- | 0.2198 | 25.0 | 37 | 0.9023 | 0.7333 |
80
- | 0.2198 | 26.0 | 39 | 0.8684 | 0.75 |
81
- | 0.1802 | 27.0 | 41 | 0.9270 | 0.6833 |
82
- | 0.1802 | 28.0 | 42 | 0.9361 | 0.6833 |
83
- | 0.1802 | 29.0 | 43 | 0.8819 | 0.7333 |
84
- | 0.1802 | 30.0 | 45 | 0.8361 | 0.75 |
85
- | 0.1802 | 31.0 | 47 | 0.8555 | 0.6833 |
86
- | 0.1802 | 32.0 | 48 | 0.8470 | 0.7 |
87
- | 0.1802 | 33.0 | 49 | 0.8418 | 0.75 |
88
- | 0.1515 | 34.0 | 51 | 0.8077 | 0.7667 |
89
- | 0.1515 | 35.0 | 53 | 0.8207 | 0.75 |
90
- | 0.1515 | 36.0 | 54 | 0.8540 | 0.7333 |
91
- | 0.1515 | 37.0 | 55 | 0.8494 | 0.7167 |
92
- | 0.1515 | 38.0 | 57 | 0.8525 | 0.75 |
93
- | 0.1515 | 39.0 | 59 | 0.8675 | 0.7167 |
94
- | 0.1313 | 40.0 | 60 | 0.8809 | 0.7167 |
95
- | 0.1313 | 41.0 | 61 | 0.8739 | 0.7333 |
96
- | 0.1313 | 42.0 | 63 | 0.8957 | 0.6833 |
97
- | 0.1313 | 43.0 | 65 | 0.9231 | 0.6833 |
98
- | 0.1313 | 44.0 | 66 | 0.9400 | 0.6833 |
99
- | 0.1313 | 45.0 | 67 | 0.9518 | 0.7 |
100
- | 0.1313 | 46.0 | 69 | 0.9820 | 0.65 |
101
- | 0.1179 | 47.0 | 71 | 0.9966 | 0.65 |
102
- | 0.1179 | 48.0 | 72 | 0.9788 | 0.6667 |
103
- | 0.1179 | 49.0 | 73 | 0.9537 | 0.6833 |
104
- | 0.1179 | 50.0 | 75 | 0.9152 | 0.7 |
105
- | 0.1179 | 51.0 | 77 | 0.8896 | 0.6833 |
106
- | 0.1179 | 52.0 | 78 | 0.8610 | 0.6667 |
107
- | 0.1179 | 53.0 | 79 | 0.8374 | 0.7 |
108
- | 0.1049 | 54.0 | 81 | 0.8419 | 0.7333 |
109
- | 0.1049 | 55.0 | 83 | 0.8516 | 0.6667 |
110
- | 0.1049 | 56.0 | 84 | 0.8241 | 0.7 |
111
- | 0.1049 | 57.0 | 85 | 0.8027 | 0.7167 |
112
- | 0.1049 | 58.0 | 87 | 0.8049 | 0.75 |
113
- | 0.1049 | 59.0 | 89 | 0.8238 | 0.75 |
114
- | 0.0973 | 60.0 | 90 | 0.8284 | 0.7167 |
115
- | 0.0973 | 61.0 | 91 | 0.8325 | 0.7 |
116
- | 0.0973 | 62.0 | 93 | 0.8268 | 0.7333 |
117
- | 0.0973 | 63.0 | 95 | 0.8333 | 0.7333 |
118
- | 0.0973 | 64.0 | 96 | 0.8424 | 0.7333 |
119
- | 0.0973 | 65.0 | 97 | 0.8505 | 0.7167 |
120
- | 0.0973 | 66.0 | 99 | 0.8644 | 0.7 |
121
- | 0.0935 | 66.6667 | 100 | 0.8673 | 0.7 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
122
 
123
 
124
  ### 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: 0.7902
21
+ - Accuracy: 0.7333
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 | 1.6064 | 0.1833 |
56
+ | No log | 2.0 | 2 | 1.6067 | 0.1667 |
57
+ | No log | 3.0 | 3 | 1.6075 | 0.1 |
58
+ | No log | 4.0 | 4 | 1.6086 | 0.2 |
59
+ | No log | 5.0 | 5 | 1.6099 | 0.1667 |
60
+ | No log | 6.0 | 6 | 1.6110 | 0.1833 |
61
+ | No log | 7.0 | 7 | 1.6132 | 0.1833 |
62
+ | No log | 8.0 | 8 | 1.6156 | 0.1667 |
63
+ | No log | 9.0 | 9 | 1.6173 | 0.25 |
64
+ | 1.5968 | 10.0 | 10 | 1.6201 | 0.2833 |
65
+ | 1.5968 | 11.0 | 11 | 1.6210 | 0.3167 |
66
+ | 1.5968 | 12.0 | 12 | 1.6208 | 0.3 |
67
+ | 1.5968 | 13.0 | 13 | 1.6162 | 0.35 |
68
+ | 1.5968 | 14.0 | 14 | 1.6076 | 0.3667 |
69
+ | 1.5968 | 15.0 | 15 | 1.5950 | 0.4 |
70
+ | 1.5968 | 16.0 | 16 | 1.5843 | 0.3833 |
71
+ | 1.5968 | 17.0 | 17 | 1.5706 | 0.4 |
72
+ | 1.5968 | 18.0 | 18 | 1.5506 | 0.4 |
73
+ | 1.5968 | 19.0 | 19 | 1.5278 | 0.4167 |
74
+ | 1.5049 | 20.0 | 20 | 1.5029 | 0.4167 |
75
+ | 1.5049 | 21.0 | 21 | 1.4745 | 0.4333 |
76
+ | 1.5049 | 22.0 | 22 | 1.4454 | 0.4667 |
77
+ | 1.5049 | 23.0 | 23 | 1.4123 | 0.4833 |
78
+ | 1.5049 | 24.0 | 24 | 1.3828 | 0.4833 |
79
+ | 1.5049 | 25.0 | 25 | 1.3580 | 0.4833 |
80
+ | 1.5049 | 26.0 | 26 | 1.3328 | 0.4833 |
81
+ | 1.5049 | 27.0 | 27 | 1.3053 | 0.4667 |
82
+ | 1.5049 | 28.0 | 28 | 1.2808 | 0.4833 |
83
+ | 1.5049 | 29.0 | 29 | 1.2581 | 0.4667 |
84
+ | 1.2782 | 30.0 | 30 | 1.2392 | 0.45 |
85
+ | 1.2782 | 31.0 | 31 | 1.2202 | 0.45 |
86
+ | 1.2782 | 32.0 | 32 | 1.1858 | 0.45 |
87
+ | 1.2782 | 33.0 | 33 | 1.1552 | 0.4667 |
88
+ | 1.2782 | 34.0 | 34 | 1.1385 | 0.4667 |
89
+ | 1.2782 | 35.0 | 35 | 1.1221 | 0.4667 |
90
+ | 1.2782 | 36.0 | 36 | 1.1088 | 0.4667 |
91
+ | 1.2782 | 37.0 | 37 | 1.0941 | 0.4667 |
92
+ | 1.2782 | 38.0 | 38 | 1.0764 | 0.4667 |
93
+ | 1.2782 | 39.0 | 39 | 1.0624 | 0.4667 |
94
+ | 1.0507 | 40.0 | 40 | 1.0446 | 0.45 |
95
+ | 1.0507 | 41.0 | 41 | 1.0348 | 0.5 |
96
+ | 1.0507 | 42.0 | 42 | 1.0177 | 0.4833 |
97
+ | 1.0507 | 43.0 | 43 | 1.0010 | 0.4667 |
98
+ | 1.0507 | 44.0 | 44 | 0.9913 | 0.4833 |
99
+ | 1.0507 | 45.0 | 45 | 0.9695 | 0.4833 |
100
+ | 1.0507 | 46.0 | 46 | 0.9485 | 0.5167 |
101
+ | 1.0507 | 47.0 | 47 | 0.9873 | 0.4667 |
102
+ | 1.0507 | 48.0 | 48 | 0.9856 | 0.4667 |
103
+ | 1.0507 | 49.0 | 49 | 0.9353 | 0.4667 |
104
+ | 0.906 | 50.0 | 50 | 0.9049 | 0.5333 |
105
+ | 0.906 | 51.0 | 51 | 0.8960 | 0.5167 |
106
+ | 0.906 | 52.0 | 52 | 0.8972 | 0.5167 |
107
+ | 0.906 | 53.0 | 53 | 0.8801 | 0.5167 |
108
+ | 0.906 | 54.0 | 54 | 0.8654 | 0.55 |
109
+ | 0.906 | 55.0 | 55 | 0.8813 | 0.55 |
110
+ | 0.906 | 56.0 | 56 | 0.8894 | 0.5333 |
111
+ | 0.906 | 57.0 | 57 | 0.8758 | 0.5333 |
112
+ | 0.906 | 58.0 | 58 | 0.8794 | 0.5333 |
113
+ | 0.906 | 59.0 | 59 | 0.8952 | 0.55 |
114
+ | 0.8081 | 60.0 | 60 | 0.8949 | 0.55 |
115
+ | 0.8081 | 61.0 | 61 | 0.8789 | 0.5833 |
116
+ | 0.8081 | 62.0 | 62 | 0.8545 | 0.6167 |
117
+ | 0.8081 | 63.0 | 63 | 0.8440 | 0.6333 |
118
+ | 0.8081 | 64.0 | 64 | 0.8344 | 0.6667 |
119
+ | 0.8081 | 65.0 | 65 | 0.8368 | 0.6333 |
120
+ | 0.8081 | 66.0 | 66 | 0.8504 | 0.6333 |
121
+ | 0.8081 | 67.0 | 67 | 0.8604 | 0.6167 |
122
+ | 0.8081 | 68.0 | 68 | 0.8637 | 0.6167 |
123
+ | 0.8081 | 69.0 | 69 | 0.8641 | 0.65 |
124
+ | 0.7364 | 70.0 | 70 | 0.8660 | 0.65 |
125
+ | 0.7364 | 71.0 | 71 | 0.8604 | 0.65 |
126
+ | 0.7364 | 72.0 | 72 | 0.8546 | 0.65 |
127
+ | 0.7364 | 73.0 | 73 | 0.8461 | 0.65 |
128
+ | 0.7364 | 74.0 | 74 | 0.8426 | 0.6833 |
129
+ | 0.7364 | 75.0 | 75 | 0.8443 | 0.6833 |
130
+ | 0.7364 | 76.0 | 76 | 0.8413 | 0.6833 |
131
+ | 0.7364 | 77.0 | 77 | 0.8385 | 0.6833 |
132
+ | 0.7364 | 78.0 | 78 | 0.8399 | 0.65 |
133
+ | 0.7364 | 79.0 | 79 | 0.8432 | 0.65 |
134
+ | 0.6787 | 80.0 | 80 | 0.8443 | 0.6167 |
135
+ | 0.6787 | 81.0 | 81 | 0.8433 | 0.6167 |
136
+ | 0.6787 | 82.0 | 82 | 0.8370 | 0.6167 |
137
+ | 0.6787 | 83.0 | 83 | 0.8315 | 0.6 |
138
+ | 0.6787 | 84.0 | 84 | 0.8275 | 0.6167 |
139
+ | 0.6787 | 85.0 | 85 | 0.8190 | 0.6333 |
140
+ | 0.6787 | 86.0 | 86 | 0.8134 | 0.6667 |
141
+ | 0.6787 | 87.0 | 87 | 0.8104 | 0.6833 |
142
+ | 0.6787 | 88.0 | 88 | 0.8108 | 0.6833 |
143
+ | 0.6787 | 89.0 | 89 | 0.8140 | 0.6833 |
144
+ | 0.6359 | 90.0 | 90 | 0.8145 | 0.6833 |
145
+ | 0.6359 | 91.0 | 91 | 0.8153 | 0.6667 |
146
+ | 0.6359 | 92.0 | 92 | 0.8135 | 0.6833 |
147
+ | 0.6359 | 93.0 | 93 | 0.8108 | 0.6833 |
148
+ | 0.6359 | 94.0 | 94 | 0.8072 | 0.6833 |
149
+ | 0.6359 | 95.0 | 95 | 0.8017 | 0.6833 |
150
+ | 0.6359 | 96.0 | 96 | 0.7965 | 0.7 |
151
+ | 0.6359 | 97.0 | 97 | 0.7928 | 0.7 |
152
+ | 0.6359 | 98.0 | 98 | 0.7908 | 0.7333 |
153
+ | 0.6359 | 99.0 | 99 | 0.7904 | 0.7333 |
154
+ | 0.6092 | 100.0 | 100 | 0.7902 | 0.7333 |
155
 
156
 
157
  ### Framework versions