emre commited on
Commit
dbf2fba
1 Parent(s): ea21d65

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-xls-r-300m-Br-small
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-xls-r-300m-Br-small
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: 1.0573
20
+ - Wer: 0.6675
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_steps: 500
48
+ - num_epochs: 30
49
+ - mixed_precision_training: Native AMP
50
+
51
+ ### Training results
52
+
53
+ | Training Loss | Epoch | Step | Validation Loss | Wer |
54
+ |:-------------:|:-----:|:----:|:---------------:|:------:|
55
+ | 5.7464 | 2.79 | 400 | 1.7474 | 1.1018 |
56
+ | 1.1117 | 5.59 | 800 | 0.9434 | 0.8697 |
57
+ | 0.6481 | 8.39 | 1200 | 0.9251 | 0.7910 |
58
+ | 0.4754 | 11.19 | 1600 | 0.9208 | 0.7412 |
59
+ | 0.3602 | 13.98 | 2000 | 0.9284 | 0.7232 |
60
+ | 0.2873 | 16.78 | 2400 | 0.9299 | 0.6940 |
61
+ | 0.2386 | 19.58 | 2800 | 1.0182 | 0.6927 |
62
+ | 0.1971 | 22.38 | 3200 | 1.0456 | 0.6898 |
63
+ | 0.1749 | 25.17 | 3600 | 1.0208 | 0.6769 |
64
+ | 0.1487 | 27.97 | 4000 | 1.0573 | 0.6675 |
65
+
66
+
67
+ ### Framework versions
68
+
69
+ - Transformers 4.11.3
70
+ - Pytorch 1.10.0+cu111
71
+ - Datasets 1.14.0
72
+ - Tokenizers 0.10.3