Hugging Face's logo

ngohuudang
/
test_bug2

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
wav2vec2
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
ngohuudang commited on
Commit
10a8abc
·
1 Parent(s): 3659d23

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +40 -21
README.md CHANGED
@@ -14,8 +14,8 @@ should probably proofread and complete it, then remove this comment. -->
14
 
15
  This model is a fine-tuned version of [nguyenvulebinh/wav2vec2-base-vietnamese-250h](https://huggingface.co/nguyenvulebinh/wav2vec2-base-vietnamese-250h) on the None dataset.
16
  It achieves the following results on the evaluation set:
17
- - Loss: 0.3549
18
- - Wer: 0.2334
19
 
20
  ## Model description
21
 
@@ -43,31 +43,50 @@ The following hyperparameters were used during training:
43
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
44
  - lr_scheduler_type: linear
45
  - lr_scheduler_warmup_steps: 500
46
- - num_epochs: 5
47
  - mixed_precision_training: Native AMP
48
 
49
  ### Training results
50
 
51
  | Training Loss | Epoch | Step | Validation Loss | Wer |
52
  |:-------------:|:-----:|:----:|:---------------:|:------:|
53
- | 0.6139 | 0.27 | 50 | 0.4498 | 0.2591 |
54
- | 0.3695 | 0.53 | 100 | 0.3626 | 0.2381 |
55
- | 0.3065 | 0.8 | 150 | 0.3484 | 0.2281 |
56
- | 0.268 | 1.07 | 200 | 0.3606 | 0.2488 |
57
- | 0.282 | 1.34 | 250 | 0.3440 | 0.2409 |
58
- | 0.2688 | 1.6 | 300 | 0.3707 | 0.2459 |
59
- | 0.2683 | 1.87 | 350 | 0.3736 | 0.2474 |
60
- | 0.2599 | 2.14 | 400 | 0.4010 | 0.2664 |
61
- | 0.2683 | 2.41 | 450 | 0.3890 | 0.2627 |
62
- | 0.2623 | 2.67 | 500 | 0.4109 | 0.2790 |
63
- | 0.2633 | 2.94 | 550 | 0.4251 | 0.2800 |
64
- | 0.2431 | 3.21 | 600 | 0.4424 | 0.2941 |
65
- | 0.2263 | 3.48 | 650 | 0.4179 | 0.2677 |
66
- | 0.2268 | 3.74 | 700 | 0.4049 | 0.2715 |
67
- | 0.1965 | 4.01 | 750 | 0.3953 | 0.2599 |
68
- | 0.1851 | 4.28 | 800 | 0.3549 | 0.2467 |
69
- | 0.1724 | 4.54 | 850 | 0.3586 | 0.2450 |
70
- | 0.1587 | 4.81 | 900 | 0.3549 | 0.2334 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
71
 
72
 
73
  ### Framework versions
 
14
 
15
  This model is a fine-tuned version of [nguyenvulebinh/wav2vec2-base-vietnamese-250h](https://huggingface.co/nguyenvulebinh/wav2vec2-base-vietnamese-250h) on the None dataset.
16
  It achieves the following results on the evaluation set:
17
+ - Loss: 0.2977
18
+ - Wer: 0.1839
19
 
20
  ## Model description
21
 
 
43
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
44
  - lr_scheduler_type: linear
45
  - lr_scheduler_warmup_steps: 500
46
+ - num_epochs: 10
47
  - mixed_precision_training: Native AMP
48
 
49
  ### Training results
50
 
51
  | Training Loss | Epoch | Step | Validation Loss | Wer |
52
  |:-------------:|:-----:|:----:|:---------------:|:------:|
53
+ | 1.1568 | 0.27 | 50 | 0.2764 | 0.1985 |
54
+ | 0.0979 | 0.53 | 100 | 0.2421 | 0.1813 |
55
+ | 0.1018 | 0.8 | 150 | 0.2420 | 0.1809 |
56
+ | 0.1011 | 1.07 | 200 | 0.2520 | 0.1992 |
57
+ | 0.0947 | 1.34 | 250 | 0.2580 | 0.1885 |
58
+ | 0.1077 | 1.6 | 300 | 0.2641 | 0.2001 |
59
+ | 0.109 | 1.87 | 350 | 0.3196 | 0.2156 |
60
+ | 0.1239 | 2.14 | 400 | 0.3298 | 0.2163 |
61
+ | 0.1286 | 2.41 | 450 | 0.3392 | 0.2436 |
62
+ | 0.1515 | 2.67 | 500 | 0.3821 | 0.2450 |
63
+ | 0.157 | 2.94 | 550 | 0.3771 | 0.2521 |
64
+ | 0.1296 | 3.21 | 600 | 0.3917 | 0.2541 |
65
+ | 0.1351 | 3.48 | 650 | 0.3670 | 0.2366 |
66
+ | 0.1387 | 3.74 | 700 | 0.3503 | 0.2347 |
67
+ | 0.1336 | 4.01 | 750 | 0.4018 | 0.2627 |
68
+ | 0.114 | 4.28 | 800 | 0.3699 | 0.2723 |
69
+ | 0.1254 | 4.54 | 850 | 0.3395 | 0.2404 |
70
+ | 0.119 | 4.81 | 900 | 0.3410 | 0.2340 |
71
+ | 0.1 | 5.08 | 950 | 0.3302 | 0.2216 |
72
+ | 0.0968 | 5.35 | 1000 | 0.3346 | 0.2255 |
73
+ | 0.0965 | 5.61 | 1050 | 0.3144 | 0.2140 |
74
+ | 0.0906 | 5.88 | 1100 | 0.3277 | 0.2109 |
75
+ | 0.0968 | 6.15 | 1150 | 0.3300 | 0.2141 |
76
+ | 0.0818 | 6.42 | 1200 | 0.3272 | 0.2085 |
77
+ | 0.0836 | 6.68 | 1250 | 0.3177 | 0.2014 |
78
+ | 0.0803 | 6.95 | 1300 | 0.3185 | 0.2005 |
79
+ | 0.0727 | 7.22 | 1350 | 0.3110 | 0.1928 |
80
+ | 0.0687 | 7.49 | 1400 | 0.3118 | 0.1965 |
81
+ | 0.0698 | 7.75 | 1450 | 0.3170 | 0.1955 |
82
+ | 0.0651 | 8.02 | 1500 | 0.3119 | 0.1929 |
83
+ | 0.0648 | 8.29 | 1550 | 0.3058 | 0.1904 |
84
+ | 0.0612 | 8.56 | 1600 | 0.3087 | 0.1935 |
85
+ | 0.0578 | 8.82 | 1650 | 0.3076 | 0.1871 |
86
+ | 0.0557 | 9.09 | 1700 | 0.3037 | 0.1862 |
87
+ | 0.0542 | 9.36 | 1750 | 0.2990 | 0.1858 |
88
+ | 0.0551 | 9.62 | 1800 | 0.2962 | 0.1837 |
89
+ | 0.0514 | 9.89 | 1850 | 0.2977 | 0.1839 |
90
 
91
 
92
  ### Framework versions