update model card README.md
Browse files
README.md
ADDED
@@ -0,0 +1,75 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
license: apache-2.0
|
3 |
+
tags:
|
4 |
+
- audio-classification
|
5 |
+
- generated_from_trainer
|
6 |
+
datasets:
|
7 |
+
- common_language
|
8 |
+
metrics:
|
9 |
+
- accuracy
|
10 |
+
model-index:
|
11 |
+
- name: wav2vec2-base-lang-id
|
12 |
+
results: []
|
13 |
+
---
|
14 |
+
|
15 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
16 |
+
should probably proofread and complete it, then remove this comment. -->
|
17 |
+
|
18 |
+
# wav2vec2-base-lang-id
|
19 |
+
|
20 |
+
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the anton-l/common_language dataset.
|
21 |
+
It achieves the following results on the evaluation set:
|
22 |
+
- Loss: 0.9836
|
23 |
+
- Accuracy: 0.7945
|
24 |
+
|
25 |
+
## Model description
|
26 |
+
|
27 |
+
More information needed
|
28 |
+
|
29 |
+
## Intended uses & limitations
|
30 |
+
|
31 |
+
More information needed
|
32 |
+
|
33 |
+
## Training and evaluation data
|
34 |
+
|
35 |
+
More information needed
|
36 |
+
|
37 |
+
## Training procedure
|
38 |
+
|
39 |
+
### Training hyperparameters
|
40 |
+
|
41 |
+
The following hyperparameters were used during training:
|
42 |
+
- learning_rate: 0.0003
|
43 |
+
- train_batch_size: 32
|
44 |
+
- eval_batch_size: 4
|
45 |
+
- seed: 0
|
46 |
+
- gradient_accumulation_steps: 4
|
47 |
+
- total_train_batch_size: 128
|
48 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
49 |
+
- lr_scheduler_type: linear
|
50 |
+
- lr_scheduler_warmup_ratio: 0.1
|
51 |
+
- num_epochs: 10.0
|
52 |
+
- mixed_precision_training: Native AMP
|
53 |
+
|
54 |
+
### Training results
|
55 |
+
|
56 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
57 |
+
|:-------------:|:-----:|:----:|:---------------:|:--------:|
|
58 |
+
| 2.9568 | 1.0 | 173 | 3.2866 | 0.1146 |
|
59 |
+
| 1.9243 | 2.0 | 346 | 2.1241 | 0.3840 |
|
60 |
+
| 1.2923 | 3.0 | 519 | 1.5498 | 0.5489 |
|
61 |
+
| 0.8659 | 4.0 | 692 | 1.4953 | 0.6126 |
|
62 |
+
| 0.5539 | 5.0 | 865 | 1.2431 | 0.6926 |
|
63 |
+
| 0.4101 | 6.0 | 1038 | 1.1443 | 0.7232 |
|
64 |
+
| 0.2945 | 7.0 | 1211 | 1.0870 | 0.7544 |
|
65 |
+
| 0.1552 | 8.0 | 1384 | 1.1080 | 0.7661 |
|
66 |
+
| 0.0968 | 9.0 | 1557 | 0.9836 | 0.7945 |
|
67 |
+
| 0.0623 | 10.0 | 1730 | 1.0252 | 0.7993 |
|
68 |
+
|
69 |
+
|
70 |
+
### Framework versions
|
71 |
+
|
72 |
+
- Transformers 4.11.0.dev0
|
73 |
+
- Pytorch 1.9.1+cu111
|
74 |
+
- Datasets 1.12.1
|
75 |
+
- Tokenizers 0.10.3
|