DewiBrynJones commited on
Commit
d6d841c
1 Parent(s): c0b4778

Model save

Browse files
Files changed (1) hide show
  1. README.md +77 -0
README.md ADDED
@@ -0,0 +1,77 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ base_model: facebook/wav2vec2-large-xlsr-53
4
+ tags:
5
+ - generated_from_trainer
6
+ metrics:
7
+ - wer
8
+ model-index:
9
+ - name: wav2vec2-xlsr-53-ft-btb-cv-other-cy
10
+ results: []
11
+ ---
12
+
13
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
14
+ should probably proofread and complete it, then remove this comment. -->
15
+
16
+ # wav2vec2-xlsr-53-ft-btb-cv-other-cy
17
+
18
+ This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset.
19
+ It achieves the following results on the evaluation set:
20
+ - Loss: 0.4934
21
+ - Wer: 0.3776
22
+
23
+ ## Model description
24
+
25
+ More information needed
26
+
27
+ ## Intended uses & limitations
28
+
29
+ More information needed
30
+
31
+ ## Training and evaluation data
32
+
33
+ More information needed
34
+
35
+ ## Training procedure
36
+
37
+ ### Training hyperparameters
38
+
39
+ The following hyperparameters were used during training:
40
+ - learning_rate: 0.0003
41
+ - train_batch_size: 8
42
+ - eval_batch_size: 64
43
+ - seed: 42
44
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
45
+ - lr_scheduler_type: linear
46
+ - lr_scheduler_warmup_steps: 800
47
+ - training_steps: 8000
48
+ - mixed_precision_training: Native AMP
49
+
50
+ ### Training results
51
+
52
+ | Training Loss | Epoch | Step | Validation Loss | Wer |
53
+ |:-------------:|:------:|:----:|:---------------:|:------:|
54
+ | 5.1054 | 0.0755 | 500 | 2.8161 | 1.0 |
55
+ | 1.4196 | 0.1509 | 1000 | 1.1687 | 0.7941 |
56
+ | 1.0028 | 0.2264 | 1500 | 0.9890 | 0.6953 |
57
+ | 0.8942 | 0.3019 | 2000 | 0.8935 | 0.6195 |
58
+ | 0.8285 | 0.3774 | 2500 | 0.8221 | 0.6075 |
59
+ | 0.763 | 0.4528 | 3000 | 0.7165 | 0.5307 |
60
+ | 0.7203 | 0.5283 | 3500 | 0.6892 | 0.5054 |
61
+ | 0.7051 | 0.6038 | 4000 | 0.6848 | 0.5070 |
62
+ | 0.6568 | 0.6792 | 4500 | 0.6342 | 0.4926 |
63
+ | 0.6315 | 0.7547 | 5000 | 0.5956 | 0.4494 |
64
+ | 0.6171 | 0.8302 | 5500 | 0.5533 | 0.4305 |
65
+ | 0.5717 | 0.9057 | 6000 | 0.5360 | 0.4212 |
66
+ | 0.5699 | 0.9811 | 6500 | 0.5184 | 0.4040 |
67
+ | 0.4905 | 1.0566 | 7000 | 0.5081 | 0.3967 |
68
+ | 0.4706 | 1.1321 | 7500 | 0.4991 | 0.3825 |
69
+ | 0.4614 | 1.2075 | 8000 | 0.4934 | 0.3776 |
70
+
71
+
72
+ ### Framework versions
73
+
74
+ - Transformers 4.44.0
75
+ - Pytorch 2.4.0+cu121
76
+ - Datasets 2.21.0
77
+ - Tokenizers 0.19.1