lgris commited on
Commit
bc1a2c8
1 Parent(s): e58d584

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +102 -0
README.md ADDED
@@ -0,0 +1,102 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ tags:
4
+ - generated_from_trainer
5
+ datasets:
6
+ - common_voice
7
+ model-index:
8
+ - name: sew-tiny-portuguese-cv8
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
+ # sew-tiny-portuguese-cv8
16
+
17
+ This model is a fine-tuned version of [lgris/sew-tiny-pt](https://huggingface.co/lgris/sew-tiny-pt) on the common_voice dataset.
18
+ It achieves the following results on the evaluation set:
19
+ - Loss: 0.4082
20
+ - Wer: 0.3053
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: 0.0001
40
+ - train_batch_size: 8
41
+ - eval_batch_size: 8
42
+ - seed: 42
43
+ - gradient_accumulation_steps: 4
44
+ - total_train_batch_size: 32
45
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
46
+ - lr_scheduler_type: linear
47
+ - lr_scheduler_warmup_steps: 1000
48
+ - training_steps: 40000
49
+ - mixed_precision_training: Native AMP
50
+
51
+ ### Training results
52
+
53
+ | Training Loss | Epoch | Step | Validation Loss | Wer |
54
+ |:-------------:|:-----:|:-----:|:---------------:|:------:|
55
+ | No log | 1.93 | 1000 | 2.9134 | 0.9767 |
56
+ | 2.9224 | 3.86 | 2000 | 2.8405 | 0.9789 |
57
+ | 2.9224 | 5.79 | 3000 | 2.8094 | 0.9800 |
58
+ | 2.8531 | 7.72 | 4000 | 2.7439 | 0.9891 |
59
+ | 2.8531 | 9.65 | 5000 | 2.7057 | 1.0159 |
60
+ | 2.7721 | 11.58 | 6000 | 2.7235 | 1.0709 |
61
+ | 2.7721 | 13.51 | 7000 | 2.5931 | 1.1035 |
62
+ | 2.6566 | 15.44 | 8000 | 2.2171 | 0.9884 |
63
+ | 2.6566 | 17.37 | 9000 | 1.2399 | 0.8081 |
64
+ | 1.9558 | 19.31 | 10000 | 0.9045 | 0.6353 |
65
+ | 1.9558 | 21.24 | 11000 | 0.7705 | 0.5533 |
66
+ | 1.4987 | 23.17 | 12000 | 0.7068 | 0.5165 |
67
+ | 1.4987 | 25.1 | 13000 | 0.6641 | 0.4718 |
68
+ | 1.3811 | 27.03 | 14000 | 0.6043 | 0.4470 |
69
+ | 1.3811 | 28.96 | 15000 | 0.5532 | 0.4268 |
70
+ | 1.2897 | 30.89 | 16000 | 0.5371 | 0.4101 |
71
+ | 1.2897 | 32.82 | 17000 | 0.5924 | 0.4150 |
72
+ | 1.225 | 34.75 | 18000 | 0.4949 | 0.3894 |
73
+ | 1.225 | 36.68 | 19000 | 0.5591 | 0.4045 |
74
+ | 1.193 | 38.61 | 20000 | 0.4927 | 0.3731 |
75
+ | 1.193 | 40.54 | 21000 | 0.4922 | 0.3712 |
76
+ | 1.1482 | 42.47 | 22000 | 0.4799 | 0.3662 |
77
+ | 1.1482 | 44.4 | 23000 | 0.4846 | 0.3648 |
78
+ | 1.1201 | 46.33 | 24000 | 0.4770 | 0.3623 |
79
+ | 1.1201 | 48.26 | 25000 | 0.4530 | 0.3426 |
80
+ | 1.0892 | 50.19 | 26000 | 0.4523 | 0.3527 |
81
+ | 1.0892 | 52.12 | 27000 | 0.4573 | 0.3443 |
82
+ | 1.0583 | 54.05 | 28000 | 0.4488 | 0.3353 |
83
+ | 1.0583 | 55.98 | 29000 | 0.4295 | 0.3285 |
84
+ | 1.0319 | 57.92 | 30000 | 0.4321 | 0.3220 |
85
+ | 1.0319 | 59.85 | 31000 | 0.4244 | 0.3236 |
86
+ | 1.0076 | 61.78 | 32000 | 0.4197 | 0.3201 |
87
+ | 1.0076 | 63.71 | 33000 | 0.4230 | 0.3208 |
88
+ | 0.9851 | 65.64 | 34000 | 0.4090 | 0.3127 |
89
+ | 0.9851 | 67.57 | 35000 | 0.4088 | 0.3133 |
90
+ | 0.9695 | 69.5 | 36000 | 0.4123 | 0.3088 |
91
+ | 0.9695 | 71.43 | 37000 | 0.4017 | 0.3090 |
92
+ | 0.9514 | 73.36 | 38000 | 0.4184 | 0.3086 |
93
+ | 0.9514 | 75.29 | 39000 | 0.4075 | 0.3043 |
94
+ | 0.944 | 77.22 | 40000 | 0.4082 | 0.3053 |
95
+
96
+
97
+ ### Framework versions
98
+
99
+ - Transformers 4.16.0.dev0
100
+ - Pytorch 1.10.1+cu102
101
+ - Datasets 1.17.1.dev0
102
+ - Tokenizers 0.11.0