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wav2vec2-large-xls-r-300m-urdu-cv-10
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice_10_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5959
- Wer: 0.3946
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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
20.8724 | 0.25 | 32 | 18.0006 | 1.0 |
10.984 | 0.5 | 64 | 6.8001 | 1.0 |
5.7792 | 0.74 | 96 | 4.9273 | 1.0 |
4.2891 | 0.99 | 128 | 3.8379 | 1.0 |
3.4937 | 1.24 | 160 | 3.2877 | 1.0 |
3.1605 | 1.49 | 192 | 3.1198 | 1.0 |
3.0874 | 1.74 | 224 | 3.0542 | 1.0 |
3.0363 | 1.98 | 256 | 3.0063 | 0.9999 |
2.9776 | 2.23 | 288 | 2.9677 | 1.0 |
2.8168 | 2.48 | 320 | 2.4189 | 1.0000 |
2.0575 | 2.73 | 352 | 1.5330 | 0.8520 |
1.4248 | 2.98 | 384 | 1.1747 | 0.7519 |
1.1354 | 3.22 | 416 | 0.9837 | 0.7047 |
1.0049 | 3.47 | 448 | 0.9414 | 0.6631 |
0.956 | 3.72 | 480 | 0.8948 | 0.6606 |
0.8906 | 3.97 | 512 | 0.8381 | 0.6291 |
0.7587 | 4.22 | 544 | 0.7714 | 0.5898 |
0.7534 | 4.47 | 576 | 0.8237 | 0.5908 |
0.7203 | 4.71 | 608 | 0.7731 | 0.5758 |
0.6876 | 4.96 | 640 | 0.7467 | 0.5390 |
0.5825 | 5.21 | 672 | 0.6940 | 0.5401 |
0.5565 | 5.46 | 704 | 0.6826 | 0.5248 |
0.5598 | 5.71 | 736 | 0.6387 | 0.5204 |
0.5289 | 5.95 | 768 | 0.6432 | 0.4956 |
0.4565 | 6.2 | 800 | 0.6643 | 0.4876 |
0.4576 | 6.45 | 832 | 0.6295 | 0.4758 |
0.4265 | 6.7 | 864 | 0.6227 | 0.4673 |
0.4359 | 6.95 | 896 | 0.6077 | 0.4598 |
0.3576 | 7.19 | 928 | 0.5800 | 0.4477 |
0.3612 | 7.44 | 960 | 0.5837 | 0.4500 |
0.345 | 7.69 | 992 | 0.5892 | 0.4466 |
0.3707 | 7.94 | 1024 | 0.6217 | 0.4380 |
0.3269 | 8.19 | 1056 | 0.5964 | 0.4412 |
0.2974 | 8.43 | 1088 | 0.6116 | 0.4394 |
0.2932 | 8.68 | 1120 | 0.5764 | 0.4235 |
0.2854 | 8.93 | 1152 | 0.5757 | 0.4239 |
0.2651 | 9.18 | 1184 | 0.5798 | 0.4253 |
0.2508 | 9.43 | 1216 | 0.5750 | 0.4316 |
0.238 | 9.67 | 1248 | 0.6038 | 0.4232 |
0.2454 | 9.92 | 1280 | 0.5781 | 0.4078 |
0.2196 | 10.17 | 1312 | 0.5931 | 0.4178 |
0.2036 | 10.42 | 1344 | 0.6134 | 0.4116 |
0.2087 | 10.67 | 1376 | 0.5831 | 0.4146 |
0.1908 | 10.91 | 1408 | 0.5987 | 0.4159 |
0.1751 | 11.16 | 1440 | 0.5968 | 0.4065 |
0.1726 | 11.41 | 1472 | 0.6037 | 0.4119 |
0.1728 | 11.66 | 1504 | 0.5961 | 0.4011 |
0.1772 | 11.91 | 1536 | 0.5903 | 0.3972 |
0.1647 | 12.16 | 1568 | 0.5960 | 0.4024 |
0.1506 | 12.4 | 1600 | 0.5986 | 0.3933 |
0.1383 | 12.65 | 1632 | 0.5893 | 0.3938 |
0.1433 | 12.9 | 1664 | 0.5999 | 0.3975 |
0.1356 | 13.15 | 1696 | 0.6035 | 0.3982 |
0.1431 | 13.4 | 1728 | 0.5997 | 0.4042 |
0.1346 | 13.64 | 1760 | 0.6018 | 0.4003 |
0.1363 | 13.89 | 1792 | 0.5891 | 0.3969 |
0.1323 | 14.14 | 1824 | 0.5983 | 0.3925 |
0.1196 | 14.39 | 1856 | 0.6003 | 0.3939 |
0.1266 | 14.64 | 1888 | 0.5997 | 0.3941 |
0.1269 | 14.88 | 1920 | 0.5959 | 0.3946 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.11.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1