Hugging Face's logo

MuhammadIqbalBazmi
/
wav2vec2-base-intent-classification-ori-f1

Audio Classification
Transformers
PyTorch
TensorBoard
wav2vec2
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
1
MuhammadIqbalBazmi commited on
Commit
cde7c51
·
1 Parent(s): f95e5c0

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +106 -0
README.md ADDED
@@ -0,0 +1,106 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ tags:
4
+ - generated_from_trainer
5
+ metrics:
6
+ - f1
7
+ model-index:
8
+ - name: wav2vec2-base-intent-classification-ori-f1
9
+ results: []
10
+ ---
11
+
12
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
13
+ should probably proofread and complete it, then remove this comment. -->
14
+
15
+ # wav2vec2-base-intent-classification-ori-f1
16
+
17
+ This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
18
+ It achieves the following results on the evaluation set:
19
+ - Loss: 1.1637
20
+ - F1: 0.7917
21
+
22
+ ## Model description
23
+
24
+ More information needed
25
+
26
+ ## Intended uses & limitations
27
+
28
+ More information needed
29
+
30
+ ## Training and evaluation data
31
+
32
+ More information needed
33
+
34
+ ## Training procedure
35
+
36
+ ### Training hyperparameters
37
+
38
+ The following hyperparameters were used during training:
39
+ - learning_rate: 3e-05
40
+ - train_batch_size: 1
41
+ - eval_batch_size: 1
42
+ - seed: 42
43
+ - gradient_accumulation_steps: 4
44
+ - total_train_batch_size: 4
45
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
46
+ - lr_scheduler_type: linear
47
+ - lr_scheduler_warmup_ratio: 0.1
48
+ - num_epochs: 45
49
+
50
+ ### Training results
51
+
52
+ | Training Loss | Epoch | Step | Validation Loss | F1 |
53
+ |:-------------:|:-----:|:----:|:---------------:|:------:|
54
+ | 2.1968 | 1.0 | 28 | 2.1818 | 0.3333 |
55
+ | 2.1592 | 2.0 | 56 | 2.0969 | 0.3333 |
56
+ | 2.0755 | 3.0 | 84 | 2.0228 | 0.3333 |
57
+ | 1.9803 | 4.0 | 112 | 1.8093 | 0.4167 |
58
+ | 1.8034 | 5.0 | 140 | 1.6328 | 0.4375 |
59
+ | 1.8118 | 6.0 | 168 | 1.5828 | 0.4583 |
60
+ | 1.583 | 7.0 | 196 | 1.5873 | 0.4375 |
61
+ | 1.4798 | 8.0 | 224 | 1.3843 | 0.5417 |
62
+ | 1.1876 | 9.0 | 252 | 1.1997 | 0.5417 |
63
+ | 1.2811 | 10.0 | 280 | 1.0566 | 0.6458 |
64
+ | 0.9653 | 11.0 | 308 | 1.0389 | 0.625 |
65
+ | 1.0774 | 12.0 | 336 | 0.8610 | 0.7292 |
66
+ | 0.8276 | 13.0 | 364 | 0.9553 | 0.6458 |
67
+ | 0.8264 | 14.0 | 392 | 0.9159 | 0.7292 |
68
+ | 0.6622 | 15.0 | 420 | 0.6933 | 0.8125 |
69
+ | 0.6244 | 16.0 | 448 | 0.6302 | 0.8333 |
70
+ | 0.4519 | 17.0 | 476 | 0.6524 | 0.8125 |
71
+ | 0.2844 | 18.0 | 504 | 0.8344 | 0.6875 |
72
+ | 0.2612 | 19.0 | 532 | 0.7528 | 0.75 |
73
+ | 0.1853 | 20.0 | 560 | 1.0809 | 0.6875 |
74
+ | 0.1259 | 21.0 | 588 | 1.0479 | 0.7083 |
75
+ | 0.0943 | 22.0 | 616 | 0.9220 | 0.7708 |
76
+ | 0.0698 | 23.0 | 644 | 1.1877 | 0.7083 |
77
+ | 0.0637 | 24.0 | 672 | 1.1921 | 0.7292 |
78
+ | 0.0507 | 25.0 | 700 | 1.0526 | 0.7708 |
79
+ | 0.047 | 26.0 | 728 | 1.0134 | 0.7917 |
80
+ | 0.0406 | 27.0 | 756 | 1.0251 | 0.7708 |
81
+ | 0.0313 | 28.0 | 784 | 1.0058 | 0.7917 |
82
+ | 0.0303 | 29.0 | 812 | 1.0468 | 0.7917 |
83
+ | 0.0251 | 30.0 | 840 | 1.0168 | 0.7917 |
84
+ | 0.0259 | 31.0 | 868 | 1.0310 | 0.7917 |
85
+ | 0.0216 | 32.0 | 896 | 1.0616 | 0.7917 |
86
+ | 0.0228 | 33.0 | 924 | 1.0887 | 0.7917 |
87
+ | 0.0208 | 34.0 | 952 | 1.7480 | 0.6458 |
88
+ | 0.0203 | 35.0 | 980 | 1.1806 | 0.7708 |
89
+ | 0.0209 | 36.0 | 1008 | 1.1815 | 0.7708 |
90
+ | 0.0182 | 37.0 | 1036 | 1.1791 | 0.7917 |
91
+ | 0.0177 | 38.0 | 1064 | 1.1730 | 0.7917 |
92
+ | 0.0165 | 39.0 | 1092 | 1.1680 | 0.7917 |
93
+ | 0.0177 | 40.0 | 1120 | 1.1642 | 0.7917 |
94
+ | 0.0176 | 41.0 | 1148 | 1.1636 | 0.7917 |
95
+ | 0.0168 | 42.0 | 1176 | 1.1638 | 0.7917 |
96
+ | 0.0166 | 43.0 | 1204 | 1.1639 | 0.7917 |
97
+ | 0.0149 | 44.0 | 1232 | 1.1636 | 0.7917 |
98
+ | 0.0149 | 45.0 | 1260 | 1.1637 | 0.7917 |
99
+
100
+
101
+ ### Framework versions
102
+
103
+ - Transformers 4.20.1
104
+ - Pytorch 1.11.0
105
+ - Datasets 2.1.0
106
+ - Tokenizers 0.12.1