|
--- |
|
language: |
|
- ur |
|
tags: |
|
- automatic-speech-recognition |
|
- mozilla-foundation/common_voice_11_0 |
|
- generated_from_trainer |
|
datasets: |
|
- common_voice_11_0 |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: wavlm-common_voice-ur |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: MOZILLA-FOUNDATION/COMMON_VOICE_11_0 - UR |
|
type: common_voice_11_0 |
|
config: ur |
|
split: test |
|
args: 'Config: ur, Training split: train+validation, Eval split: test' |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 0.37805822235986375 |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# wavlm-common_voice-ur |
|
|
|
This model is a fine-tuned version of [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) on the MOZILLA-FOUNDATION/COMMON_VOICE_11_0 - UR dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: inf |
|
- Wer: 0.3781 |
|
|
|
## Model description |
|
|
|
More information needed |
|
|
|
## Intended uses & limitations |
|
|
|
More information needed |
|
|
|
## Training and evaluation data |
|
|
|
More information needed |
|
|
|
## Training procedure |
|
|
|
### Training hyperparameters |
|
|
|
The following hyperparameters were used during training: |
|
- learning_rate: 0.0003 |
|
- train_batch_size: 4 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- num_devices: 2 |
|
- total_train_batch_size: 8 |
|
- total_eval_batch_size: 16 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 500 |
|
- num_epochs: 15.0 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:-----:|:---------------:|:------:| |
|
| 4.9073 | 0.11 | 100 | inf | 1.0 | |
|
| 3.3187 | 0.22 | 200 | inf | 1.0 | |
|
| 2.9683 | 0.32 | 300 | inf | 0.9991 | |
|
| 2.454 | 0.43 | 400 | inf | 0.9915 | |
|
| 1.1169 | 0.54 | 500 | inf | 0.7906 | |
|
| 1.5943 | 0.65 | 600 | inf | 0.7260 | |
|
| 0.9991 | 0.75 | 700 | inf | 0.7305 | |
|
| 1.0608 | 0.86 | 800 | inf | 0.6655 | |
|
| 1.4739 | 0.97 | 900 | inf | 0.6120 | |
|
| 0.8682 | 1.08 | 1000 | inf | 0.6087 | |
|
| 0.8025 | 1.18 | 1100 | inf | 0.5991 | |
|
| 0.8468 | 1.29 | 1200 | inf | 0.5605 | |
|
| 0.5896 | 1.4 | 1300 | inf | 0.5550 | |
|
| 0.6304 | 1.51 | 1400 | inf | 0.5441 | |
|
| 0.6533 | 1.61 | 1500 | inf | 0.5297 | |
|
| 0.7636 | 1.72 | 1600 | inf | 0.5210 | |
|
| 0.5155 | 1.83 | 1700 | inf | 0.5331 | |
|
| 0.6266 | 1.94 | 1800 | inf | 0.5182 | |
|
| 0.4286 | 2.05 | 1900 | inf | 0.4956 | |
|
| 0.527 | 2.15 | 2000 | inf | 0.4935 | |
|
| 0.4919 | 2.26 | 2100 | inf | 0.4933 | |
|
| 0.3977 | 2.37 | 2200 | inf | 0.5015 | |
|
| 0.5349 | 2.48 | 2300 | inf | 0.4942 | |
|
| 0.5066 | 2.58 | 2400 | inf | 0.4684 | |
|
| 0.6734 | 2.69 | 2500 | inf | 0.4870 | |
|
| 0.5411 | 2.8 | 2600 | inf | 0.4919 | |
|
| 0.3451 | 2.91 | 2700 | inf | 0.4607 | |
|
| 0.3913 | 3.01 | 2800 | inf | 0.4558 | |
|
| 0.3046 | 3.12 | 2900 | inf | 0.4685 | |
|
| 0.2954 | 3.23 | 3000 | inf | 0.4638 | |
|
| 0.5469 | 3.34 | 3100 | inf | 0.4495 | |
|
| 0.2334 | 3.44 | 3200 | inf | 0.4547 | |
|
| 0.3119 | 3.55 | 3300 | inf | 0.4619 | |
|
| 0.6393 | 3.66 | 3400 | inf | 0.4541 | |
|
| 0.4133 | 3.77 | 3500 | inf | 0.4456 | |
|
| 0.4946 | 3.88 | 3600 | inf | 0.4369 | |
|
| 0.3484 | 3.98 | 3700 | inf | 0.4335 | |
|
| 0.3996 | 4.09 | 3800 | inf | 0.4717 | |
|
| 0.2754 | 4.2 | 3900 | inf | 0.4414 | |
|
| 0.3141 | 4.31 | 4000 | inf | 0.4390 | |
|
| 0.2231 | 4.41 | 4100 | inf | 0.4353 | |
|
| 0.2673 | 4.52 | 4200 | inf | 0.4410 | |
|
| 0.2911 | 4.63 | 4300 | inf | 0.4337 | |
|
| 0.3643 | 4.74 | 4400 | inf | 0.4362 | |
|
| 0.2706 | 4.84 | 4500 | inf | 0.4359 | |
|
| 0.2464 | 4.95 | 4600 | inf | 0.4249 | |
|
| 0.1453 | 5.06 | 4700 | inf | 0.4293 | |
|
| 0.2619 | 5.17 | 4800 | inf | 0.4201 | |
|
| 0.1888 | 5.27 | 4900 | inf | 0.4222 | |
|
| 0.2571 | 5.38 | 5000 | inf | 0.4333 | |
|
| 0.1653 | 5.49 | 5100 | inf | 0.4192 | |
|
| 0.2102 | 5.6 | 5200 | inf | 0.4232 | |
|
| 0.1456 | 5.71 | 5300 | inf | 0.4198 | |
|
| 0.3314 | 5.81 | 5400 | inf | 0.4169 | |
|
| 0.1703 | 5.92 | 5500 | inf | 0.4118 | |
|
| 0.1546 | 6.03 | 5600 | inf | 0.4147 | |
|
| 0.2065 | 6.14 | 5700 | inf | 0.4291 | |
|
| 0.1792 | 6.24 | 5800 | inf | 0.4175 | |
|
| 0.2433 | 6.35 | 5900 | inf | 0.4157 | |
|
| 0.352 | 6.46 | 6000 | inf | 0.4083 | |
|
| 0.2406 | 6.57 | 6100 | inf | 0.4341 | |
|
| 0.2397 | 6.67 | 6200 | inf | 0.4185 | |
|
| 0.2145 | 6.78 | 6300 | inf | 0.4147 | |
|
| 0.1733 | 6.89 | 6400 | inf | 0.4150 | |
|
| 0.1867 | 7.0 | 6500 | inf | 0.4154 | |
|
| 0.612 | 7.1 | 6600 | inf | 0.4159 | |
|
| 0.1413 | 7.21 | 6700 | inf | 0.4162 | |
|
| 0.2074 | 7.32 | 6800 | inf | 0.4146 | |
|
| 0.1362 | 7.43 | 6900 | inf | 0.4087 | |
|
| 0.2971 | 7.53 | 7000 | inf | 0.4061 | |
|
| 0.1443 | 7.64 | 7100 | inf | 0.4132 | |
|
| 0.3066 | 7.75 | 7200 | inf | 0.4059 | |
|
| 0.2163 | 7.86 | 7300 | inf | 0.4026 | |
|
| 0.1251 | 7.97 | 7400 | inf | 0.4022 | |
|
| 0.154 | 8.07 | 7500 | inf | 0.3980 | |
|
| 0.1809 | 8.18 | 7600 | inf | 0.4030 | |
|
| 0.0985 | 8.29 | 7700 | inf | 0.3992 | |
|
| 0.1672 | 8.4 | 7800 | inf | 0.4049 | |
|
| 0.1508 | 8.5 | 7900 | inf | 0.3985 | |
|
| 0.1893 | 8.61 | 8000 | inf | 0.3999 | |
|
| 0.1045 | 8.72 | 8100 | inf | 0.4014 | |
|
| 0.2569 | 8.83 | 8200 | inf | 0.3976 | |
|
| 0.2654 | 8.93 | 8300 | inf | 0.4021 | |
|
| 0.0641 | 9.04 | 8400 | inf | 0.3964 | |
|
| 0.1145 | 9.15 | 8500 | inf | 0.3995 | |
|
| 0.1808 | 9.26 | 8600 | inf | 0.3960 | |
|
| 0.0766 | 9.36 | 8700 | inf | 0.3938 | |
|
| 0.1537 | 9.47 | 8800 | inf | 0.3909 | |
|
| 0.2864 | 9.58 | 8900 | inf | 0.4028 | |
|
| 0.1372 | 9.69 | 9000 | inf | 0.3970 | |
|
| 0.06 | 9.8 | 9100 | inf | 0.3911 | |
|
| 0.0831 | 9.9 | 9200 | inf | 0.3954 | |
|
| 0.1469 | 10.01 | 9300 | inf | 0.3952 | |
|
| 0.0683 | 10.12 | 9400 | inf | 0.3899 | |
|
| 0.0694 | 10.23 | 9500 | inf | 0.3918 | |
|
| 0.0919 | 10.33 | 9600 | inf | 0.3895 | |
|
| 0.1842 | 10.44 | 9700 | inf | 0.3945 | |
|
| 0.0581 | 10.55 | 9800 | inf | 0.3979 | |
|
| 0.1397 | 10.66 | 9900 | inf | 0.3911 | |
|
| 0.0657 | 10.76 | 10000 | inf | 0.3886 | |
|
| 0.1316 | 10.87 | 10100 | inf | 0.3877 | |
|
| 0.1434 | 10.98 | 10200 | inf | 0.3858 | |
|
| 0.05 | 11.09 | 10300 | inf | 0.3842 | |
|
| 0.0565 | 11.19 | 10400 | inf | 0.3873 | |
|
| 0.1696 | 11.3 | 10500 | inf | 0.3873 | |
|
| 0.0819 | 11.41 | 10600 | inf | 0.3901 | |
|
| 0.0631 | 11.52 | 10700 | inf | 0.3927 | |
|
| 0.1276 | 11.63 | 10800 | inf | 0.3868 | |
|
| 0.1002 | 11.73 | 10900 | inf | 0.3848 | |
|
| 0.081 | 11.84 | 11000 | inf | 0.3873 | |
|
| 0.1745 | 11.95 | 11100 | inf | 0.3895 | |
|
| 0.097 | 12.06 | 11200 | inf | 0.4021 | |
|
| 0.0875 | 12.16 | 11300 | inf | 0.3876 | |
|
| 0.027 | 12.27 | 11400 | inf | 0.3873 | |
|
| 0.0859 | 12.38 | 11500 | inf | 0.3863 | |
|
| 0.1192 | 12.49 | 11600 | inf | 0.3799 | |
|
| 0.1055 | 12.59 | 11700 | inf | 0.3795 | |
|
| 0.0603 | 12.7 | 11800 | inf | 0.3785 | |
|
| 0.111 | 12.81 | 11900 | inf | 0.3783 | |
|
| 0.0313 | 12.92 | 12000 | inf | 0.3800 | |
|
| 0.0241 | 13.02 | 12100 | inf | 0.3796 | |
|
| 0.1072 | 13.13 | 12200 | inf | 0.3803 | |
|
| 0.1758 | 13.24 | 12300 | inf | 0.3809 | |
|
| 0.1334 | 13.35 | 12400 | inf | 0.3794 | |
|
| 0.1372 | 13.46 | 12500 | inf | 0.3798 | |
|
| 0.1919 | 13.56 | 12600 | inf | 0.3791 | |
|
| 0.1753 | 13.67 | 12700 | inf | 0.3781 | |
|
| 0.294 | 13.78 | 12800 | inf | 0.3788 | |
|
| 0.3132 | 13.89 | 12900 | inf | 0.3786 | |
|
| 0.0486 | 13.99 | 13000 | inf | 0.3778 | |
|
| 0.1199 | 14.1 | 13100 | inf | 0.3777 | |
|
| 0.0381 | 14.21 | 13200 | inf | 0.3808 | |
|
| 0.0875 | 14.32 | 13300 | inf | 0.3795 | |
|
| 0.0122 | 14.42 | 13400 | inf | 0.3797 | |
|
| 0.1417 | 14.53 | 13500 | inf | 0.3780 | |
|
| 0.1754 | 14.64 | 13600 | inf | 0.3788 | |
|
| 0.0426 | 14.75 | 13700 | inf | 0.3780 | |
|
| 0.0309 | 14.85 | 13800 | inf | 0.3787 | |
|
| 0.1447 | 14.96 | 13900 | inf | 0.3796 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.27.0.dev0 |
|
- Pytorch 1.13.1 |
|
- Datasets 2.8.0 |
|
- Tokenizers 0.13.2 |
|
|
