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badrex / xlsr-he
Model's Last Updated: June 07 2024
automatic-speech-recognition
Introduction of xlsr-he
Model Details of xlsr-he
xlsr-he
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
- Loss: 1.1042
- Wer: 0.5618
- Cer: 0.1990
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: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 4.8209 | 0.8368 | 100 | 4.9679 | 1.0 | 1.0 |
| 3.197 | 1.6736 | 200 | 3.5446 | 1.0 | 1.0 |
| 3.3296 | 2.5105 | 300 | 3.4076 | 1.0 | 1.0 |
| 2.3184 | 3.3473 | 400 | 2.7358 | 1.0137 | 0.6925 |
| 1.058 | 4.1841 | 500 | 1.4893 | 0.9039 | 0.4332 |
| 0.7087 | 5.0209 | 600 | 1.2311 | 0.8541 | 0.3847 |
| 0.5416 | 5.8577 | 700 | 1.0641 | 0.8256 | 0.3603 |
| 0.5273 | 6.6946 | 800 | 1.1168 | 0.8699 | 0.3384 |
| 0.5321 | 7.5314 | 900 | 1.1116 | 0.8200 | 0.3271 |
| 0.3195 | 8.3682 | 1000 | 1.0792 | 0.8480 | 0.3287 |
| 0.2597 | 9.2050 | 1100 | 1.0042 | 0.7433 | 0.3017 |
| 0.3101 | 10.0418 | 1200 | 1.0282 | 0.7255 | 0.2903 |
| 0.2546 | 10.8787 | 1300 | 0.9019 | 0.7265 | 0.2759 |
| 0.1811 | 11.7155 | 1400 | 1.0079 | 0.7107 | 0.2734 |
| 0.1583 | 12.5523 | 1500 | 1.1007 | 0.7356 | 0.2847 |
| 0.1904 | 13.3891 | 1600 | 1.1371 | 0.6843 | 0.2708 |
| 0.1575 | 14.2259 | 1700 | 1.1959 | 0.6889 | 0.2704 |
| 0.1265 | 15.0628 | 1800 | 1.1985 | 0.7428 | 0.2853 |
| 0.113 | 15.8996 | 1900 | 1.1250 | 0.6762 | 0.2611 |
| 0.17 | 16.7364 | 2000 | 1.1427 | 0.6980 | 0.2695 |
| 0.1124 | 17.5732 | 2100 | 1.1954 | 0.7062 | 0.2720 |
| 0.1232 | 18.4100 | 2200 | 1.1302 | 0.6706 | 0.2495 |
| 0.1115 | 19.2469 | 2300 | 1.1399 | 0.6741 | 0.2604 |
| 0.1016 | 20.0837 | 2400 | 1.1784 | 0.6441 | 0.2436 |
| 0.1455 | 20.9205 | 2500 | 1.2145 | 0.6751 | 0.2485 |
| 0.074 | 21.7573 | 2600 | 1.2742 | 0.6304 | 0.2545 |
| 0.0654 | 22.5941 | 2700 | 1.0912 | 0.6146 | 0.2266 |
| 0.1123 | 23.4310 | 2800 | 1.0622 | 0.6350 | 0.2352 |
| 0.1563 | 24.2678 | 2900 | 1.0540 | 0.6416 | 0.2318 |
| 0.0716 | 25.1046 | 3000 | 1.0769 | 0.6304 | 0.2331 |
| 0.1085 | 25.9414 | 3100 | 1.0909 | 0.5979 | 0.2212 |
| 0.1026 | 26.7782 | 3200 | 1.1154 | 0.6075 | 0.2227 |
| 0.0872 | 27.6151 | 3300 | 1.1303 | 0.6268 | 0.2301 |
| 0.0761 | 28.4519 | 3400 | 1.0749 | 0.6187 | 0.2300 |
| 0.1127 | 29.2887 | 3500 | 1.0718 | 0.6121 | 0.2205 |
| 0.0598 | 30.1255 | 3600 | 1.1657 | 0.6223 | 0.2264 |
| 0.096 | 30.9623 | 3700 | 1.1789 | 0.5938 | 0.2179 |
| 0.075 | 31.7992 | 3800 | 1.2492 | 0.6380 | 0.2350 |
| 0.057 | 32.6360 | 3900 | 1.2094 | 0.6263 | 0.2274 |
| 0.1077 | 33.4728 | 4000 | 1.1825 | 0.6040 | 0.2209 |
| 0.0455 | 34.3096 | 4100 | 1.1660 | 0.6136 | 0.2201 |
| 0.0688 | 35.1464 | 4200 | 1.1257 | 0.6050 | 0.2191 |
| 0.064 | 35.9833 | 4300 | 1.1346 | 0.5867 | 0.2122 |
| 0.0383 | 36.8201 | 4400 | 1.1975 | 0.6009 | 0.2180 |
| 0.0397 | 37.6569 | 4500 | 1.1697 | 0.5989 | 0.2177 |
| 0.0447 | 38.4937 | 4600 | 1.2174 | 0.6040 | 0.2186 |
| 0.0545 | 39.3305 | 4700 | 1.1958 | 0.5994 | 0.2184 |
| 0.0531 | 40.1674 | 4800 | 1.1707 | 0.5902 | 0.2127 |
| 0.1481 | 41.0042 | 4900 | 1.1475 | 0.5770 | 0.2071 |
| 0.0427 | 41.8410 | 5000 | 1.1719 | 0.5892 | 0.2114 |
| 0.0242 | 42.6778 | 5100 | 1.0977 | 0.5740 | 0.2053 |
| 0.0398 | 43.5146 | 5200 | 1.1135 | 0.5694 | 0.2063 |
| 0.037 | 44.3515 | 5300 | 1.1234 | 0.5735 | 0.2086 |
| 0.0255 | 45.1883 | 5400 | 1.1127 | 0.5740 | 0.2040 |
| 0.0467 | 46.0251 | 5500 | 1.1123 | 0.5653 | 0.1998 |
| 0.0261 | 46.8619 | 5600 | 1.1039 | 0.5719 | 0.2008 |
| 0.0512 | 47.6987 | 5700 | 1.1167 | 0.5679 | 0.2011 |
| 0.0551 | 48.5356 | 5800 | 1.1126 | 0.5648 | 0.1990 |
| 0.0373 | 49.3724 | 5900 | 1.1042 | 0.5618 | 0.1990 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
Runs of badrex xlsr-he on huggingface.co
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Updated:March 28 2026
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