许可证：apache-2.0
标签：
- 自动语音识别
- gary109/AI_Light_Dance
- 训练生成
模型索引：
- 名称：ai-light-dance_chord_ft_wav2vec2-large-xlsr-53
结果：[]
ai-light-dance_chord_ft_wav2vec2-large-xlsr-53
该模型是基于facebook/wav2vec2-large-xlsr-53在GARY109/AI_Light_Dance - ONSET-CHORD2数据集上微调的版本。
在评估集上取得了以下结果：
- 损失：1.8722
- 词错误率（Wer）：0.9590
模型描述
需要更多信息
预期用途与限制
需要更多信息
训练与评估数据
需要更多信息
训练过程
训练超参数
训练过程中使用了以下超参数：
- 学习率：3e-05
- 训练批次大小：10
- 评估批次大小：10
- 随机种子：42
- 梯度累积步数：16
- 总训练批次大小：160
- 优化器：Adam，参数beta=(0.9,0.999)，epsilon=1e-08
- 学习率调度器类型：线性
- 学习率预热步数：100
- 训练轮数：50.0
- 混合精度训练：原生AMP
训练结果
| 训练损失 |
轮次 |
步数 |
验证损失 |
词错误率 |
| 5.1857 |
1.0 |
126 |
4.5913 |
1.0 |
| 3.0939 |
2.0 |
252 |
3.0160 |
1.0 |
| 2.8403 |
3.0 |
378 |
2.7337 |
1.0 |
| 2.2525 |
4.0 |
504 |
2.5588 |
0.9825 |
| 2.0291 |
5.0 |
630 |
2.5216 |
0.9701 |
| 1.9083 |
6.0 |
756 |
2.3990 |
0.9514 |
| 1.8745 |
7.0 |
882 |
2.2781 |
0.9474 |
| 1.8222 |
8.0 |
1008 |
2.2360 |
0.9471 |
| 1.7871 |
9.0 |
1134 |
2.1960 |
0.9463 |
| 1.7225 |
10.0 |
1260 |
2.0775 |
0.9464 |
| 1.6856 |
11.0 |
1386 |
2.0817 |
0.9518 |
| 1.6903 |
12.0 |
1512 |
2.0607 |
0.9534 |
| 1.6034 |
13.0 |
1638 |
1.9956 |
0.9504 |
| 1.6171 |
14.0 |
1764 |
2.0099 |
0.9490 |
| 1.5508 |
15.0 |
1890 |
2.0424 |
0.9591 |
| 1.539 |
16.0 |
2016 |
1.9728 |
0.9600 |
| 1.5176 |
17.0 |
2142 |
2.0421 |
0.9628 |
| 1.5088 |
18.0 |
2268 |
1.9428 |
0.9598 |
| 1.4739 |
19.0 |
2394 |
1.9886 |
0.9591 |
| 1.4228 |
20.0 |
2520 |
2.0164 |
0.9670 |
| 1.4277 |
21.0 |
2646 |
1.9968 |
0.9704 |
| 1.3834 |
22.0 |
2772 |
1.9882 |
0.9669 |
| 1.3768 |
23.0 |
2898 |
1.9519 |
0.9606 |
| 1.3747 |
24.0 |
3024 |
1.8923 |
0.9580 |
| 1.3533 |
25.0 |
3150 |
1.9767 |
0.9707 |
| 1.3312 |
26.0 |
3276 |
1.8993 |
0.9609 |
| 1.2743 |
27.0 |
3402 |
1.9494 |
0.9705 |
| 1.2924 |
28.0 |
3528 |
1.9019 |
0.9631 |
| 1.2621 |
29.0 |
3654 |
1.9110 |
0.9596 |
| 1.2387 |
30.0 |
3780 |
1.9118 |
0.9627 |
| 1.228 |
31.0 |
3906 |
1.8722 |
0.9590 |
| 1.1938 |
32.0 |
4032 |
1.8890 |
0.9599 |
| 1.1887 |
33.0 |
4158 |
1.9175 |
0.9653 |
| 1.1807 |
34.0 |
4284 |
1.8983 |
0.9649 |
| 1.1553 |
35.0 |
4410 |
1.9246 |
0.9703 |
| 1.1448 |
36.0 |
4536 |
1.9248 |
0.9705 |
| 1.1146 |
37.0 |
4662 |
1.9747 |
0.9804 |
| 1.1394 |
38.0 |
4788 |
1.9119 |
0.9723 |
| 1.1206 |
39.0 |
4914 |
1.8931 |
0.9630 |
| 1.0892 |
40.0 |
5040 |
1.9243 |
0.9668 |
| 1.104 |
41.0 |
5166 |
1.8965 |
0.9671 |
| 1.054 |
42.0 |
5292 |
1.9477 |
0.9755 |
| 1.0922 |
43.0 |
5418 |
1.8969 |
0.9699 |
| 1.0484 |
44.0 |
5544 |
1.9423 |
0.9733 |
| 1.0567 |
45.0 |
5670 |
1.9412 |
0.9745 |
| 1.0615 |
46.0 |
5796 |
1.9076 |
0.9674 |
| 1.0201 |
47.0 |
5922 |
1.9384 |
0.9743 |
| 1.0664 |
48.0 |
6048 |
1.9509 |
0.9816 |
| 1.0498 |
49.0 |
6174 |
1.9426 |
0.9757 |
| 1.0303 |
50.0 |
6300 |
1.9477 |
0.9781 |
框架版本
- Transformers 4.21.0.dev0
- Pytorch 1.9.1+cu102
- Datasets 2.3.3.dev0
- Tokenizers 0.12.1
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