anuragshas commited on
Commit
d297d9f
·
1 Parent(s): 87eccaa

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +72 -0
README.md ADDED
@@ -0,0 +1,72 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ tags:
4
+ - generated_from_trainer
5
+ datasets:
6
+ - common_voice
7
+ model-index:
8
+ - name: wav2vec2-large-xls-r-300m-as
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-large-xls-r-300m-as
16
+
17
+ This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
18
+ It achieves the following results on the evaluation set:
19
+ - Loss: 1.9068
20
+ - Wer: 0.6679
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: 0.0003
40
+ - train_batch_size: 16
41
+ - eval_batch_size: 8
42
+ - seed: 42
43
+ - gradient_accumulation_steps: 2
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_ratio: 0.12
48
+ - num_epochs: 240
49
+
50
+ ### Training results
51
+
52
+ | Training Loss | Epoch | Step | Validation Loss | Wer |
53
+ |:-------------:|:------:|:----:|:---------------:|:------:|
54
+ | 5.7027 | 21.05 | 400 | 3.4157 | 1.0 |
55
+ | 1.1638 | 42.1 | 800 | 1.3498 | 0.7461 |
56
+ | 0.2266 | 63.15 | 1200 | 1.6147 | 0.7273 |
57
+ | 0.1473 | 84.21 | 1600 | 1.6649 | 0.7108 |
58
+ | 0.1043 | 105.26 | 2000 | 1.7691 | 0.7090 |
59
+ | 0.0779 | 126.31 | 2400 | 1.8300 | 0.7009 |
60
+ | 0.0613 | 147.36 | 2800 | 1.8681 | 0.6916 |
61
+ | 0.0471 | 168.41 | 3200 | 1.8567 | 0.6875 |
62
+ | 0.0343 | 189.46 | 3600 | 1.9054 | 0.6840 |
63
+ | 0.0265 | 210.51 | 4000 | 1.9020 | 0.6786 |
64
+ | 0.0219 | 231.56 | 4400 | 1.9068 | 0.6679 |
65
+
66
+
67
+ ### Framework versions
68
+
69
+ - Transformers 4.15.0
70
+ - Pytorch 1.10.0+cu111
71
+ - Datasets 1.17.0
72
+ - Tokenizers 0.10.3