🚀 aradia-ctc-v1
這個模型是 /l/users/abdulwahab.sahyoun/aradia/aradia-ctc-v1 在 ABDUSAHMBZUAI/ARABIC_SPEECH_MASSIVE_300HRS - NA 數據集上的微調版本。它在評估集上取得了以下結果:
- 損失值(Loss):0.7171
- 字錯率(Wer):0.3336
🚀 快速開始
本模型為自動語音識別領域的模型,基於特定數據集微調而來,可用於阿拉伯語語音識別任務。
🔧 技術細節
訓練超參數
訓練過程中使用了以下超參數:
- 學習率(learning_rate):0.0003
- 訓練批次大小(train_batch_size):32
- 評估批次大小(eval_batch_size):32
- 隨機種子(seed):42
- 梯度累積步數(gradient_accumulation_steps):2
- 總訓練批次大小(total_train_batch_size):64
- 優化器(optimizer):Adam,其中 betas=(0.9, 0.999),epsilon=1e-08
- 學習率調度器類型(lr_scheduler_type):線性
- 學習率調度器熱身步數(lr_scheduler_warmup_steps):500
- 訓練輪數(num_epochs):20.0
- 混合精度訓練(mixed_precision_training):Native AMP
訓練結果
訓練損失 |
輪數 |
步數 |
驗證損失 |
字錯率 |
無日誌記錄 |
0.22 |
100 |
5.1889 |
1.0 |
無日誌記錄 |
0.43 |
200 |
3.1129 |
1.0 |
無日誌記錄 |
0.65 |
300 |
3.0503 |
1.0 |
無日誌記錄 |
0.87 |
400 |
3.0279 |
1.0 |
6.2756 |
1.09 |
500 |
2.9965 |
1.0 |
6.2756 |
1.3 |
600 |
2.3618 |
0.9993 |
6.2756 |
1.52 |
700 |
1.2715 |
0.8758 |
6.2756 |
1.74 |
800 |
0.9971 |
0.7156 |
6.2756 |
1.96 |
900 |
0.8927 |
0.6382 |
1.712 |
2.17 |
1000 |
0.8252 |
0.5926 |
1.712 |
2.39 |
1100 |
0.7794 |
0.5434 |
1.712 |
2.61 |
1200 |
0.7557 |
0.5092 |
1.712 |
2.83 |
1300 |
0.7347 |
0.5203 |
1.712 |
3.04 |
1400 |
0.7189 |
0.4929 |
0.9305 |
3.26 |
1500 |
0.6820 |
0.4595 |
0.9305 |
3.48 |
1600 |
0.6792 |
0.4504 |
0.9305 |
3.69 |
1700 |
0.6596 |
0.4442 |
0.9305 |
3.91 |
1800 |
0.6756 |
0.4432 |
0.9305 |
4.13 |
1900 |
0.6663 |
0.4392 |
0.737 |
4.35 |
2000 |
0.6479 |
0.4372 |
0.737 |
4.56 |
2100 |
0.6353 |
0.4203 |
0.737 |
4.78 |
2200 |
0.6251 |
0.4088 |
0.737 |
5.0 |
2300 |
0.6209 |
0.4177 |
0.737 |
5.22 |
2400 |
0.6639 |
0.4094 |
0.6247 |
5.43 |
2500 |
0.6408 |
0.3970 |
0.6247 |
5.65 |
2600 |
0.6373 |
0.3932 |
0.6247 |
5.87 |
2700 |
0.6411 |
0.3928 |
0.6247 |
6.09 |
2800 |
0.6378 |
0.3897 |
0.6247 |
6.3 |
2900 |
0.6396 |
0.3929 |
0.5443 |
6.52 |
3000 |
0.6544 |
0.3864 |
0.5443 |
6.74 |
3100 |
0.6218 |
0.3786 |
0.5443 |
6.96 |
3200 |
0.6200 |
0.3784 |
0.5443 |
7.17 |
3300 |
0.6157 |
0.3791 |
0.5443 |
7.39 |
3400 |
0.6317 |
0.3798 |
0.4845 |
7.61 |
3500 |
0.6540 |
0.3771 |
0.4845 |
7.83 |
3600 |
0.6436 |
0.3670 |
0.4845 |
8.04 |
3700 |
0.6335 |
0.3695 |
0.4845 |
8.26 |
3800 |
0.6579 |
0.3610 |
0.4845 |
8.48 |
3900 |
0.6170 |
0.3613 |
0.4279 |
8.69 |
4000 |
0.6523 |
0.3617 |
0.4279 |
8.91 |
4100 |
0.6349 |
0.3577 |
0.4279 |
9.13 |
4200 |
0.6344 |
0.3673 |
0.4279 |
9.35 |
4300 |
0.6215 |
0.3641 |
0.4279 |
9.56 |
4400 |
0.6513 |
0.3608 |
0.3825 |
9.78 |
4500 |
0.6386 |
0.3605 |
0.3825 |
10.0 |
4600 |
0.6724 |
0.3549 |
0.3825 |
10.22 |
4700 |
0.6776 |
0.3602 |
0.3825 |
10.43 |
4800 |
0.6739 |
0.3544 |
0.3825 |
10.65 |
4900 |
0.6688 |
0.3557 |
0.3477 |
10.87 |
5000 |
0.6674 |
0.3564 |
0.3477 |
11.09 |
5100 |
0.6786 |
0.3476 |
0.3477 |
11.3 |
5200 |
0.6818 |
0.3478 |
0.3477 |
11.52 |
5300 |
0.6874 |
0.3470 |
0.3477 |
11.74 |
5400 |
0.6993 |
0.3424 |
0.3101 |
11.96 |
5500 |
0.6950 |
0.3404 |
0.3101 |
12.17 |
5600 |
0.6872 |
0.3406 |
0.3101 |
12.39 |
5700 |
0.6846 |
0.3424 |
0.3101 |
12.61 |
5800 |
0.7051 |
0.3405 |
0.3101 |
12.83 |
5900 |
0.7051 |
0.3378 |
0.2859 |
13.04 |
6000 |
0.6955 |
0.3403 |
0.2859 |
13.26 |
6100 |
0.7115 |
0.3390 |
0.2859 |
13.48 |
6200 |
0.7074 |
0.3384 |
0.2859 |
13.69 |
6300 |
0.7002 |
0.3376 |
0.2859 |
13.91 |
6400 |
0.7171 |
0.3360 |
0.2714 |
14.13 |
6500 |
0.7193 |
0.3341 |
0.2714 |
14.35 |
6600 |
0.7132 |
0.3347 |
0.2714 |
14.56 |
6700 |
0.7184 |
0.3353 |
0.2714 |
14.78 |
6800 |
0.7171 |
0.3331 |
框架版本
- Transformers 4.18.0.dev0
- Pytorch 1.10.2+cu113
- Datasets 1.18.4
- Tokenizers 0.11.6