unza commited on
Commit
f499b22
1 Parent(s): 289a004

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +65 -0
README.md ADDED
@@ -0,0 +1,65 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ tags:
4
+ - generated_from_trainer
5
+ model-index:
6
+ - name: wav2vec2-xls-r-300m-nyanja-test_v2
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-xls-r-300m-nyanja-test_v2
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: inf
18
+ - Wer: 0.3734
19
+ - Cer: 0.0827
20
+
21
+ ## Model description
22
+
23
+ More information needed
24
+
25
+ ## Intended uses & limitations
26
+
27
+ More information needed
28
+
29
+ ## Training and evaluation data
30
+
31
+ More information needed
32
+
33
+ ## Training procedure
34
+
35
+ ### Training hyperparameters
36
+
37
+ The following hyperparameters were used during training:
38
+ - learning_rate: 0.001
39
+ - train_batch_size: 4
40
+ - eval_batch_size: 8
41
+ - seed: 42
42
+ - gradient_accumulation_steps: 2
43
+ - total_train_batch_size: 8
44
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
45
+ - lr_scheduler_type: linear
46
+ - lr_scheduler_warmup_steps: 400
47
+ - num_epochs: 15
48
+ - mixed_precision_training: Native AMP
49
+
50
+ ### Training results
51
+
52
+ | Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
53
+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
54
+ | 1.5816 | 0.62 | 400 | inf | 0.5702 | 0.1373 |
55
+ | 0.6341 | 1.24 | 800 | inf | 0.4383 | 0.1022 |
56
+ | 0.5103 | 1.86 | 1200 | inf | 0.3782 | 0.0895 |
57
+ | 0.4553 | 2.48 | 1600 | inf | 0.3734 | 0.0827 |
58
+
59
+
60
+ ### Framework versions
61
+
62
+ - Transformers 4.17.0
63
+ - Pytorch 1.12.1+cu113
64
+ - Datasets 1.18.3
65
+ - Tokenizers 0.13.2