Hugging Face's logo

sil-ai
/
w2v2-kaqchikel

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Kaqchikel
wav2vec2
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
DCNemesis commited on
Commit
13c4309
·
1 Parent(s): 58cabbc

update to latest model with Bloom

Browse files
Files changed (9) hide show
  1. .gitignore +1 -0
  2. README.md +61 -35
  3. added_tokens.json +1 -1
  4. config.json +2 -2
  5. pytorch_model.bin +2 -2
  6. runs/May12_21-11-05_dba5a7e4a756/1652389925.8010192/events.out.tfevents.1652389925.dba5a7e4a756.80.1 +3 -0
  7. runs/May12_21-11-05_dba5a7e4a756/events.out.tfevents.1652389925.dba5a7e4a756.80.0 +3 -0
  8. training_args.bin +1 -1
  9. vocab.json +1 -1
.gitignore ADDED
@@ -0,0 +1 @@
 
 
1
+ checkpoint-*/
README.md CHANGED
@@ -3,20 +3,20 @@ license: apache-2.0
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
- - name: wav2vec2-large-xls-r-300m-kaqchikel
7
  results: []
8
  ---
9
 
10
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
11
  should probably proofread and complete it, then remove this comment. -->
12
 
13
- # wav2vec2-large-xls-r-300m-kaqchikel
14
 
15
  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.
16
  It achieves the following results on the evaluation set:
17
- - Loss: 2.7944
18
- - Cer: 0.3042
19
- - Wer: 0.6409
20
 
21
  ## Model description
22
 
@@ -51,39 +51,65 @@ The following hyperparameters were used during training:
51
 
52
  | Training Loss | Epoch | Step | Validation Loss | Cer | Wer |
53
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
54
- | 8.2725 | 3.56 | 100 | 3.2834 | 1.0 | 1.0 |
55
- | 3.3088 | 7.14 | 200 | 3.0773 | 1.0 | 1.0 |
56
- | 3.1588 | 10.7 | 300 | 3.1077 | 1.0 | 1.0 |
57
- | 3.0761 | 14.28 | 400 | 2.8695 | 0.9655 | 1.0 |
58
- | 2.1863 | 17.84 | 500 | 1.7030 | 0.4362 | 0.9421 |
59
- | 1.2297 | 21.42 | 600 | 1.7189 | 0.3418 | 0.7567 |
60
- | 0.8466 | 24.98 | 700 | 2.0529 | 0.3435 | 0.7656 |
61
- | 0.5978 | 28.56 | 800 | 1.9337 | 0.3343 | 0.7226 |
62
- | 0.4197 | 32.14 | 900 | 2.0655 | 0.3228 | 0.7018 |
63
- | 0.3161 | 35.7 | 1000 | 2.1808 | 0.3265 | 0.7033 |
64
- | 0.2511 | 39.28 | 1100 | 2.2830 | 0.3284 | 0.6973 |
65
- | 0.199 | 42.84 | 1200 | 2.3076 | 0.3181 | 0.6810 |
66
- | 0.1828 | 46.42 | 1300 | 2.5238 | 0.3123 | 0.6409 |
67
- | 0.1536 | 49.98 | 1400 | 2.3768 | 0.3123 | 0.6736 |
68
- | 0.1305 | 53.56 | 1500 | 2.4302 | 0.3139 | 0.6617 |
69
- | 0.1221 | 57.14 | 1600 | 2.4143 | 0.3134 | 0.6588 |
70
- | 0.1077 | 60.7 | 1700 | 2.5522 | 0.3095 | 0.6513 |
71
- | 0.0942 | 64.28 | 1800 | 2.5287 | 0.3053 | 0.6528 |
72
- | 0.0809 | 67.84 | 1900 | 2.6239 | 0.3075 | 0.6350 |
73
- | 0.0735 | 71.42 | 2000 | 2.6427 | 0.3036 | 0.6261 |
74
- | 0.0696 | 74.98 | 2100 | 2.7212 | 0.3145 | 0.6484 |
75
- | 0.0606 | 78.56 | 2200 | 2.6362 | 0.3178 | 0.6543 |
76
- | 0.0545 | 82.14 | 2300 | 2.6754 | 0.3084 | 0.6365 |
77
- | 0.0505 | 85.7 | 2400 | 2.7123 | 0.3111 | 0.6380 |
78
- | 0.0465 | 89.28 | 2500 | 2.7157 | 0.3125 | 0.6291 |
79
- | 0.0427 | 92.84 | 2600 | 2.8010 | 0.3078 | 0.6320 |
80
- | 0.0429 | 96.42 | 2700 | 2.7976 | 0.3067 | 0.6395 |
81
- | 0.0384 | 99.98 | 2800 | 2.7944 | 0.3042 | 0.6409 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
82
 
83
 
84
  ### Framework versions
85
 
86
  - Transformers 4.11.3
87
- - Pytorch 1.10.0+cu111
88
- - Datasets 2.1.0
89
  - Tokenizers 0.10.3
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: wav2vec2-large-xls-r-300m-kaqchikel-with-bloom
7
  results: []
8
  ---
9
 
10
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
11
  should probably proofread and complete it, then remove this comment. -->
12
 
13
+ # wav2vec2-large-xls-r-300m-kaqchikel-with-bloom
14
 
15
  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.
16
  It achieves the following results on the evaluation set:
17
+ - Loss: 0.6700
18
+ - Cer: 0.0854
19
+ - Wer: 0.3069
20
 
21
  ## Model description
22
 
 
51
 
52
  | Training Loss | Epoch | Step | Validation Loss | Cer | Wer |
53
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
54
+ | 11.1557 | 1.84 | 100 | 4.2251 | 1.0 | 1.0 |
55
+ | 3.7231 | 3.7 | 200 | 3.5794 | 1.0 | 1.0 |
56
+ | 3.3076 | 5.55 | 300 | 3.4362 | 1.0 | 1.0 |
57
+ | 3.2495 | 7.4 | 400 | 3.2553 | 1.0 | 1.0 |
58
+ | 3.2076 | 9.26 | 500 | 3.2932 | 1.0 | 1.0 |
59
+ | 3.1304 | 11.11 | 600 | 3.1100 | 1.0 | 1.0 |
60
+ | 2.899 | 12.95 | 700 | 2.4021 | 0.8477 | 1.0 |
61
+ | 2.2875 | 14.81 | 800 | 1.5473 | 0.4790 | 0.9984 |
62
+ | 1.7605 | 16.66 | 900 | 1.1034 | 0.3061 | 0.9192 |
63
+ | 1.3802 | 18.51 | 1000 | 0.9422 | 0.2386 | 0.8530 |
64
+ | 1.0989 | 20.37 | 1100 | 0.7429 | 0.1667 | 0.6042 |
65
+ | 0.857 | 22.22 | 1200 | 0.7490 | 0.1499 | 0.5751 |
66
+ | 0.6899 | 24.07 | 1300 | 0.6376 | 0.1286 | 0.4798 |
67
+ | 0.5927 | 25.92 | 1400 | 0.6887 | 0.1232 | 0.4443 |
68
+ | 0.4699 | 27.77 | 1500 | 0.6341 | 0.1184 | 0.4378 |
69
+ | 0.4029 | 29.62 | 1600 | 0.6341 | 0.1103 | 0.4216 |
70
+ | 0.3492 | 31.48 | 1700 | 0.6709 | 0.1121 | 0.4120 |
71
+ | 0.3019 | 33.33 | 1800 | 0.7665 | 0.1097 | 0.4136 |
72
+ | 0.2681 | 35.18 | 1900 | 0.6671 | 0.1085 | 0.4120 |
73
+ | 0.2491 | 37.04 | 2000 | 0.7049 | 0.1010 | 0.3748 |
74
+ | 0.2108 | 38.88 | 2100 | 0.6699 | 0.1064 | 0.3974 |
75
+ | 0.2146 | 40.73 | 2200 | 0.7037 | 0.1046 | 0.3780 |
76
+ | 0.1854 | 42.59 | 2300 | 0.6970 | 0.1055 | 0.4006 |
77
+ | 0.1693 | 44.44 | 2400 | 0.6593 | 0.0980 | 0.3764 |
78
+ | 0.1628 | 46.29 | 2500 | 0.7162 | 0.0998 | 0.3764 |
79
+ | 0.156 | 48.15 | 2600 | 0.6445 | 0.0998 | 0.3829 |
80
+ | 0.1439 | 49.99 | 2700 | 0.6437 | 0.1004 | 0.3845 |
81
+ | 0.1292 | 51.84 | 2800 | 0.6471 | 0.0944 | 0.3457 |
82
+ | 0.1287 | 53.7 | 2900 | 0.6411 | 0.0923 | 0.3538 |
83
+ | 0.1186 | 55.55 | 3000 | 0.6754 | 0.0992 | 0.3813 |
84
+ | 0.1175 | 57.4 | 3100 | 0.6741 | 0.0953 | 0.3538 |
85
+ | 0.1082 | 59.26 | 3200 | 0.6949 | 0.0977 | 0.3619 |
86
+ | 0.105 | 61.11 | 3300 | 0.6919 | 0.0983 | 0.3683 |
87
+ | 0.1048 | 62.95 | 3400 | 0.6802 | 0.0950 | 0.3425 |
88
+ | 0.092 | 64.81 | 3500 | 0.6830 | 0.0962 | 0.3263 |
89
+ | 0.0904 | 66.66 | 3600 | 0.6993 | 0.0971 | 0.3554 |
90
+ | 0.0914 | 68.51 | 3700 | 0.6932 | 0.0995 | 0.3554 |
91
+ | 0.0823 | 70.37 | 3800 | 0.6742 | 0.0950 | 0.3409 |
92
+ | 0.0799 | 72.22 | 3900 | 0.6852 | 0.0917 | 0.3279 |
93
+ | 0.0767 | 74.07 | 4000 | 0.6684 | 0.0929 | 0.3489 |
94
+ | 0.0736 | 75.92 | 4100 | 0.6611 | 0.0923 | 0.3393 |
95
+ | 0.0708 | 77.77 | 4200 | 0.7123 | 0.0944 | 0.3393 |
96
+ | 0.0661 | 79.62 | 4300 | 0.6577 | 0.0899 | 0.3247 |
97
+ | 0.0651 | 81.48 | 4400 | 0.6671 | 0.0869 | 0.3150 |
98
+ | 0.0607 | 83.33 | 4500 | 0.6980 | 0.0893 | 0.3231 |
99
+ | 0.0552 | 85.18 | 4600 | 0.6947 | 0.0884 | 0.3183 |
100
+ | 0.0574 | 87.04 | 4700 | 0.6652 | 0.0899 | 0.3183 |
101
+ | 0.0503 | 88.88 | 4800 | 0.6798 | 0.0863 | 0.3053 |
102
+ | 0.0479 | 90.73 | 4900 | 0.6690 | 0.0884 | 0.3166 |
103
+ | 0.0483 | 92.59 | 5000 | 0.6789 | 0.0872 | 0.3069 |
104
+ | 0.0437 | 94.44 | 5100 | 0.6758 | 0.0875 | 0.3069 |
105
+ | 0.0458 | 96.29 | 5200 | 0.6662 | 0.0884 | 0.3102 |
106
+ | 0.0434 | 98.15 | 5300 | 0.6699 | 0.0881 | 0.3069 |
107
+ | 0.0449 | 99.99 | 5400 | 0.6700 | 0.0854 | 0.3069 |
108
 
109
 
110
  ### Framework versions
111
 
112
  - Transformers 4.11.3
113
+ - Pytorch 1.10.0+cu113
114
+ - Datasets 2.2.1
115
  - Tokenizers 0.10.3
added_tokens.json CHANGED
@@ -1 +1 @@
1
- {"<s>": 41, "</s>": 42}
 
1
+ {"<s>": 43, "</s>": 44}
config.json CHANGED
@@ -70,10 +70,10 @@
70
  "num_feat_extract_layers": 7,
71
  "num_hidden_layers": 24,
72
  "num_negatives": 100,
73
- "pad_token_id": 40,
74
  "proj_codevector_dim": 768,
75
  "torch_dtype": "float32",
76
  "transformers_version": "4.11.3",
77
  "use_weighted_layer_sum": false,
78
- "vocab_size": 43
79
  }
 
70
  "num_feat_extract_layers": 7,
71
  "num_hidden_layers": 24,
72
  "num_negatives": 100,
73
+ "pad_token_id": 42,
74
  "proj_codevector_dim": 768,
75
  "torch_dtype": "float32",
76
  "transformers_version": "4.11.3",
77
  "use_weighted_layer_sum": false,
78
+ "vocab_size": 45
79
  }
pytorch_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:3214e3a78df562de8e26f41e1614f2f0a0276682720647dbb9f7557bd72ee39c
3
- size 1262099953
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:283610f07e4df61975befd33fcb80d3f551c0d105527fc588f26c259ab792ff8
3
+ size 1262108145
runs/May12_21-11-05_dba5a7e4a756/1652389925.8010192/events.out.tfevents.1652389925.dba5a7e4a756.80.1 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:aba2a7db40c50b1f714a1c6be441dbd4bfcaaeb0747bdf67516a60b3bb850aff
3
+ size 4603
runs/May12_21-11-05_dba5a7e4a756/events.out.tfevents.1652389925.dba5a7e4a756.80.0 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6eaba39c0a5bb7077ae11d63b4d327376333aeb6d59178b14b32c9bcbd18253b
3
+ size 32789
training_args.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:43b1f442364671a9d9696d575f2424d0ff8be67c429a0827edf24dcd8e523568
3
  size 2863
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0acdc598758bb3df495301eca1526cab3f8a37bc3aaa7e9828ded67bb12e6e9e
3
  size 2863
vocab.json CHANGED
@@ -1 +1 @@
1
- {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5, "f": 6, "g": 7, "h": 8, "i": 9, "j": 10, "k": 11, "l": 12, "m": 13, "n": 14, "o": 15, "p": 16, "q": 17, "r": 18, "s": 19, "t": 20, "u": 21, "v": 22, "w": 23, "x": 24, "y": 25, "z": 26, "á": 27, "ä": 28, "é": 29, "ë": 30, "í": 31, "ï": 32, "ñ": 33, "ó": 34, "ö": 35, "ú": 36, "ü": 37, "’": 38, "|": 0, "[UNK]": 39, "[PAD]": 40}
 
1
+ {"+": 1, "/": 2, "a": 3, "b": 4, "c": 5, "d": 6, "e": 7, "f": 8, "g": 9, "h": 10, "i": 11, "j": 12, "k": 13, "l": 14, "m": 15, "n": 16, "o": 17, "p": 18, "q": 19, "r": 20, "s": 21, "t": 22, "u": 23, "v": 24, "w": 25, "x": 26, "y": 27, "z": 28, "á": 29, "ä": 30, "é": 31, "ë": 32, "í": 33, "ï": 34, "ñ": 35, "ó": 36, "ö": 37, "ú": 38, "ü": 39, "’": 40, "|": 0, "[UNK]": 41, "[PAD]": 42}