Hugging Face's logo

nrshoudi
/
wav2vec2-large-xls-r-300m-Arabic-phoneme

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
wav2vec2
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
8
nrshoudi commited on
Commit
b624a0f
•
1 Parent(s): 2a603b9

Model save

Browse files
Files changed (1) hide show
  1. README.md +39 -36
README.md CHANGED
@@ -3,6 +3,8 @@ license: apache-2.0
3
  base_model: facebook/wav2vec2-xls-r-300m
4
  tags:
5
  - generated_from_trainer
 
 
6
  model-index:
7
  - name: wav2vec2-large-xls-r-300m-Arabic-phoneme
8
  results: []
@@ -13,10 +15,11 @@ should probably proofread and complete it, then remove this comment. -->
13
 
14
  # wav2vec2-large-xls-r-300m-Arabic-phoneme
15
 
16
- This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
17
  It achieves the following results on the evaluation set:
18
- - Loss: 0.0365
19
- - Per: 0.0138
 
20
 
21
  ## Model description
22
 
@@ -48,43 +51,43 @@ The following hyperparameters were used during training:
48
 
49
  ### Training results
50
 
51
- | Training Loss | Epoch | Step | Validation Loss | Per |
52
- |:-------------:|:-----:|:----:|:---------------:|:------:|
53
- | 5.3526 | 1.0 | 102 | 2.1537 | 1.0 |
54
- | 2.0368 | 2.0 | 204 | 2.0887 | 1.0 |
55
- | 2.0267 | 3.0 | 306 | 2.0675 | 1.0 |
56
- | 1.9965 | 4.0 | 408 | 1.9867 | 0.9940 |
57
- | 1.9372 | 5.0 | 510 | 1.8724 | 0.9825 |
58
- | 1.7146 | 6.0 | 612 | 1.6606 | 0.9913 |
59
- | 1.6576 | 7.0 | 714 | 1.6004 | 0.9933 |
60
- | 1.4857 | 8.0 | 816 | 1.3504 | 0.9871 |
61
- | 1.117 | 9.0 | 918 | 0.8836 | 0.8882 |
62
- | 0.6447 | 10.0 | 1020 | 0.4553 | 0.4092 |
63
- | 0.3553 | 11.0 | 1122 | 0.2485 | 0.1743 |
64
- | 0.2193 | 12.0 | 1224 | 0.1664 | 0.0711 |
65
- | 0.1677 | 13.0 | 1326 | 0.1392 | 0.0621 |
66
- | 0.1317 | 14.0 | 1428 | 0.1072 | 0.0418 |
67
- | 0.1203 | 15.0 | 1530 | 0.0975 | 0.0361 |
68
- | 0.1079 | 16.0 | 1632 | 0.0936 | 0.0314 |
69
- | 0.0902 | 17.0 | 1734 | 0.0762 | 0.0254 |
70
- | 0.0835 | 18.0 | 1836 | 0.0609 | 0.0229 |
71
- | 0.0691 | 19.0 | 1938 | 0.0592 | 0.0223 |
72
- | 0.0665 | 20.0 | 2040 | 0.0601 | 0.0229 |
73
- | 0.0599 | 21.0 | 2142 | 0.0469 | 0.0179 |
74
- | 0.0545 | 22.0 | 2244 | 0.0520 | 0.0203 |
75
- | 0.047 | 23.0 | 2346 | 0.0450 | 0.0163 |
76
- | 0.0409 | 24.0 | 2448 | 0.0449 | 0.0181 |
77
- | 0.0401 | 25.0 | 2550 | 0.0431 | 0.0160 |
78
- | 0.0403 | 26.0 | 2652 | 0.0419 | 0.0164 |
79
- | 0.0351 | 27.0 | 2754 | 0.0360 | 0.0143 |
80
- | 0.0324 | 28.0 | 2856 | 0.0386 | 0.0145 |
81
- | 0.0311 | 29.0 | 2958 | 0.0367 | 0.0139 |
82
- | 0.028 | 30.0 | 3060 | 0.0365 | 0.0138 |
83
 
84
 
85
  ### Framework versions
86
 
87
- - Transformers 4.32.1
88
  - Pytorch 2.0.1+cu118
89
  - Datasets 1.18.3
90
  - Tokenizers 0.13.3
 
3
  base_model: facebook/wav2vec2-xls-r-300m
4
  tags:
5
  - generated_from_trainer
6
+ metrics:
7
+ - wer
8
  model-index:
9
  - name: wav2vec2-large-xls-r-300m-Arabic-phoneme
10
  results: []
 
15
 
16
  # wav2vec2-large-xls-r-300m-Arabic-phoneme
17
 
18
+ This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on an unknown dataset.
19
  It achieves the following results on the evaluation set:
20
+ - Loss: 0.0335
21
+ - Per: 0.0199
22
+ - Wer: 0.0225
23
 
24
  ## Model description
25
 
 
51
 
52
  ### Training results
53
 
54
+ | Training Loss | Epoch | Step | Validation Loss | Per | Wer |
55
+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
56
+ | 5.3718 | 1.0 | 102 | 2.1140 | 1.0 | 1.0 |
57
+ | 2.036 | 2.0 | 204 | 2.0637 | 1.0 | 1.0 |
58
+ | 2.0175 | 3.0 | 306 | 2.1252 | 1.0 | 1.0 |
59
+ | 1.9463 | 4.0 | 408 | 1.7014 | 0.9942 | 0.9887 |
60
+ | 1.702 | 5.0 | 510 | 1.7257 | 0.9944 | 0.9892 |
61
+ | 1.6475 | 6.0 | 612 | 1.5855 | 0.9897 | 0.9798 |
62
+ | 1.4766 | 7.0 | 714 | 1.2777 | 0.9787 | 0.9641 |
63
+ | 1.0363 | 8.0 | 816 | 0.7926 | 0.7738 | 0.7731 |
64
+ | 0.5964 | 9.0 | 918 | 0.4220 | 0.3994 | 0.4133 |
65
+ | 0.3437 | 10.0 | 1020 | 0.2307 | 0.1387 | 0.1549 |
66
+ | 0.2052 | 11.0 | 1122 | 0.1587 | 0.0645 | 0.0738 |
67
+ | 0.1509 | 12.0 | 1224 | 0.1314 | 0.0464 | 0.0544 |
68
+ | 0.1256 | 13.0 | 1326 | 0.1070 | 0.0448 | 0.0518 |
69
+ | 0.0935 | 14.0 | 1428 | 0.0854 | 0.0394 | 0.0452 |
70
+ | 0.0779 | 15.0 | 1530 | 0.0896 | 0.0376 | 0.0440 |
71
+ | 0.0674 | 16.0 | 1632 | 0.0625 | 0.0255 | 0.0306 |
72
+ | 0.0558 | 17.0 | 1734 | 0.0573 | 0.0270 | 0.0318 |
73
+ | 0.0492 | 18.0 | 1836 | 0.0542 | 0.0248 | 0.0288 |
74
+ | 0.0486 | 19.0 | 1938 | 0.0631 | 0.0336 | 0.0369 |
75
+ | 0.047 | 20.0 | 2040 | 0.0482 | 0.0255 | 0.0290 |
76
+ | 0.0432 | 21.0 | 2142 | 0.0470 | 0.0262 | 0.0307 |
77
+ | 0.0433 | 22.0 | 2244 | 0.0460 | 0.0250 | 0.0290 |
78
+ | 0.0367 | 23.0 | 2346 | 0.0450 | 0.0253 | 0.0295 |
79
+ | 0.0343 | 24.0 | 2448 | 0.0444 | 0.0254 | 0.0283 |
80
+ | 0.0292 | 25.0 | 2550 | 0.0427 | 0.0248 | 0.0283 |
81
+ | 0.0261 | 26.0 | 2652 | 0.0409 | 0.0220 | 0.0250 |
82
+ | 0.025 | 27.0 | 2754 | 0.0360 | 0.0221 | 0.0251 |
83
+ | 0.0236 | 28.0 | 2856 | 0.0350 | 0.0208 | 0.0231 |
84
+ | 0.0222 | 29.0 | 2958 | 0.0338 | 0.0199 | 0.0222 |
85
+ | 0.0202 | 30.0 | 3060 | 0.0335 | 0.0199 | 0.0225 |
86
 
87
 
88
  ### Framework versions
89
 
90
+ - Transformers 4.33.1
91
  - Pytorch 2.0.1+cu118
92
  - Datasets 1.18.3
93
  - Tokenizers 0.13.3