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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-large-xlsr-53 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_17_0 |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-large-xlsr-Mongolian-cv17-base |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: common_voice_17_0 |
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type: common_voice_17_0 |
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config: mn |
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split: validation |
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args: mn |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.6570458404074703 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# wav2vec2-large-xlsr-Mongolian-cv17-base |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_17_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1550 |
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- Wer: 0.6570 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0003 |
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- train_batch_size: 32 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 80 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-------:|:----:|:---------------:|:------:| |
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| No log | 0.5882 | 20 | 12.9741 | 1.0 | |
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| No log | 1.1765 | 40 | 12.7936 | 1.0002 | |
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| No log | 1.7647 | 60 | 12.3703 | 1.0 | |
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| No log | 2.3529 | 80 | 5.6880 | 1.0 | |
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| No log | 2.9412 | 100 | 3.6853 | 1.0 | |
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| No log | 3.5294 | 120 | 3.3076 | 1.0 | |
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| No log | 4.1176 | 140 | 3.2023 | 1.0 | |
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| No log | 4.7059 | 160 | 3.1422 | 1.0 | |
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| No log | 5.2941 | 180 | 3.1331 | 1.0 | |
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| No log | 5.8824 | 200 | 3.1183 | 1.0 | |
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| No log | 6.4706 | 220 | 3.1175 | 1.0 | |
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| No log | 7.0588 | 240 | 3.1132 | 1.0 | |
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| No log | 7.6471 | 260 | 3.1111 | 1.0 | |
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| No log | 8.2353 | 280 | 3.1101 | 1.0 | |
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| No log | 8.8235 | 300 | 3.1135 | 1.0 | |
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| No log | 9.4118 | 320 | 3.1039 | 1.0 | |
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| No log | 10.0 | 340 | 3.0961 | 1.0 | |
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| No log | 10.5882 | 360 | 3.0809 | 1.0 | |
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| No log | 11.1765 | 380 | 3.0651 | 1.0 | |
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| 4.9312 | 11.7647 | 400 | 3.0478 | 1.0 | |
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| 4.9312 | 12.3529 | 420 | 3.0584 | 1.0 | |
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| 4.9312 | 12.9412 | 440 | 3.0064 | 1.0 | |
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| 4.9312 | 13.5294 | 460 | 2.8224 | 1.0 | |
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| 4.9312 | 14.1176 | 480 | 2.5811 | 1.0 | |
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| 4.9312 | 14.7059 | 500 | 2.1769 | 1.0032 | |
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| 4.9312 | 15.2941 | 520 | 1.7646 | 1.0742 | |
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| 4.9312 | 15.8824 | 540 | 1.4124 | 1.0159 | |
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| 4.9312 | 16.4706 | 560 | 1.2848 | 0.9538 | |
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| 4.9312 | 17.0588 | 580 | 1.2267 | 0.9808 | |
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| 4.9312 | 17.6471 | 600 | 1.1108 | 0.9423 | |
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| 4.9312 | 18.2353 | 620 | 1.1815 | 0.9678 | |
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| 4.9312 | 18.8235 | 640 | 1.0553 | 0.8896 | |
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| 4.9312 | 19.4118 | 660 | 1.0977 | 0.8884 | |
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| 4.9312 | 20.0 | 680 | 0.9775 | 0.8532 | |
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| 4.9312 | 20.5882 | 700 | 0.9972 | 0.8340 | |
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| 4.9312 | 21.1765 | 720 | 1.0438 | 0.8009 | |
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| 4.9312 | 21.7647 | 740 | 0.9990 | 0.7850 | |
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| 4.9312 | 22.3529 | 760 | 0.9693 | 0.7595 | |
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| 4.9312 | 22.9412 | 780 | 1.0659 | 0.7699 | |
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| 1.3568 | 23.5294 | 800 | 0.9913 | 0.7610 | |
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| 1.3568 | 24.1176 | 820 | 1.0340 | 0.7547 | |
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| 1.3568 | 24.7059 | 840 | 1.0347 | 0.7337 | |
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| 1.3568 | 25.2941 | 860 | 1.0703 | 0.7437 | |
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| 1.3568 | 25.8824 | 880 | 1.0441 | 0.7350 | |
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| 1.3568 | 26.4706 | 900 | 1.0683 | 0.7261 | |
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| 1.3568 | 27.0588 | 920 | 1.0231 | 0.7296 | |
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| 1.3568 | 27.6471 | 940 | 1.0517 | 0.7291 | |
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| 1.3568 | 28.2353 | 960 | 1.1089 | 0.7417 | |
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| 1.3568 | 28.8235 | 980 | 1.0957 | 0.7223 | |
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| 1.3568 | 29.4118 | 1000 | 1.1120 | 0.7258 | |
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| 1.3568 | 30.0 | 1020 | 1.0992 | 0.7396 | |
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| 1.3568 | 30.5882 | 1040 | 1.1502 | 0.7190 | |
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| 1.3568 | 31.1765 | 1060 | 1.0743 | 0.7225 | |
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| 1.3568 | 31.7647 | 1080 | 1.0548 | 0.7178 | |
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| 1.3568 | 32.3529 | 1100 | 1.0534 | 0.7104 | |
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| 1.3568 | 32.9412 | 1120 | 1.0752 | 0.7083 | |
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| 1.3568 | 33.5294 | 1140 | 1.1574 | 0.7160 | |
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| 1.3568 | 34.1176 | 1160 | 1.1471 | 0.7190 | |
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| 1.3568 | 34.7059 | 1180 | 1.1077 | 0.7093 | |
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| 0.2559 | 35.2941 | 1200 | 1.0737 | 0.7004 | |
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| 0.2559 | 35.8824 | 1220 | 1.0822 | 0.6905 | |
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| 0.2559 | 36.4706 | 1240 | 1.0836 | 0.6889 | |
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| 0.2559 | 37.0588 | 1260 | 1.1399 | 0.6975 | |
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| 0.2559 | 37.6471 | 1280 | 1.0981 | 0.6880 | |
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| 0.2559 | 38.2353 | 1300 | 1.0887 | 0.6938 | |
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| 0.2559 | 38.8235 | 1320 | 1.0870 | 0.7112 | |
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| 0.2559 | 39.4118 | 1340 | 1.1324 | 0.6978 | |
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| 0.2559 | 40.0 | 1360 | 1.1170 | 0.6834 | |
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| 0.2559 | 40.5882 | 1380 | 1.1032 | 0.6761 | |
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| 0.2559 | 41.1765 | 1400 | 1.1361 | 0.7035 | |
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| 0.2559 | 41.7647 | 1420 | 1.0855 | 0.6965 | |
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| 0.2559 | 42.3529 | 1440 | 1.1320 | 0.6933 | |
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| 0.2559 | 42.9412 | 1460 | 1.1194 | 0.6849 | |
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| 0.2559 | 43.5294 | 1480 | 1.0870 | 0.6912 | |
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| 0.2559 | 44.1176 | 1500 | 1.1434 | 0.6785 | |
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| 0.2559 | 44.7059 | 1520 | 1.1434 | 0.6926 | |
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| 0.2559 | 45.2941 | 1540 | 1.1703 | 0.6839 | |
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| 0.2559 | 45.8824 | 1560 | 1.1275 | 0.6762 | |
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| 0.2559 | 46.4706 | 1580 | 1.1511 | 0.6840 | |
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| 0.1626 | 47.0588 | 1600 | 1.1336 | 0.6771 | |
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| 0.1626 | 47.6471 | 1620 | 1.1421 | 0.6785 | |
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| 0.1626 | 48.2353 | 1640 | 1.1084 | 0.6831 | |
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| 0.1626 | 48.8235 | 1660 | 1.1682 | 0.6831 | |
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| 0.1626 | 49.4118 | 1680 | 1.1349 | 0.6763 | |
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| 0.1626 | 50.0 | 1700 | 1.1561 | 0.6793 | |
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| 0.1626 | 50.5882 | 1720 | 1.1117 | 0.6660 | |
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| 0.1626 | 51.1765 | 1740 | 1.1875 | 0.6834 | |
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| 0.1626 | 51.7647 | 1760 | 1.1453 | 0.6782 | |
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| 0.1626 | 52.3529 | 1780 | 1.1040 | 0.6744 | |
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| 0.1626 | 52.9412 | 1800 | 1.1213 | 0.6711 | |
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| 0.1626 | 53.5294 | 1820 | 1.1454 | 0.6689 | |
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| 0.1626 | 54.1176 | 1840 | 1.1659 | 0.6706 | |
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| 0.1626 | 54.7059 | 1860 | 1.1616 | 0.6823 | |
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| 0.1626 | 55.2941 | 1880 | 1.2440 | 0.6817 | |
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| 0.1626 | 55.8824 | 1900 | 1.1472 | 0.6753 | |
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| 0.1626 | 56.4706 | 1920 | 1.1588 | 0.6691 | |
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| 0.1626 | 57.0588 | 1940 | 1.1590 | 0.6731 | |
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| 0.1626 | 57.6471 | 1960 | 1.1649 | 0.6712 | |
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| 0.1626 | 58.2353 | 1980 | 1.1990 | 0.6680 | |
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| 0.123 | 58.8235 | 2000 | 1.1282 | 0.6681 | |
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| 0.123 | 59.4118 | 2020 | 1.1609 | 0.6686 | |
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| 0.123 | 60.0 | 2040 | 1.1722 | 0.6703 | |
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| 0.123 | 60.5882 | 2060 | 1.1538 | 0.6739 | |
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| 0.123 | 61.1765 | 2080 | 1.1679 | 0.6727 | |
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| 0.123 | 61.7647 | 2100 | 1.1747 | 0.6687 | |
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| 0.123 | 62.3529 | 2120 | 1.1716 | 0.6691 | |
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| 0.123 | 62.9412 | 2140 | 1.1785 | 0.6655 | |
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| 0.123 | 63.5294 | 2160 | 1.1485 | 0.6658 | |
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| 0.123 | 64.1176 | 2180 | 1.1578 | 0.6626 | |
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| 0.123 | 64.7059 | 2200 | 1.1694 | 0.6648 | |
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| 0.123 | 65.2941 | 2220 | 1.1711 | 0.6677 | |
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| 0.123 | 65.8824 | 2240 | 1.1581 | 0.6624 | |
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| 0.123 | 66.4706 | 2260 | 1.1650 | 0.6723 | |
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| 0.123 | 67.0588 | 2280 | 1.1789 | 0.6637 | |
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| 0.123 | 67.6471 | 2300 | 1.1705 | 0.6624 | |
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| 0.123 | 68.2353 | 2320 | 1.1071 | 0.6615 | |
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| 0.123 | 68.8235 | 2340 | 1.1300 | 0.6654 | |
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| 0.123 | 69.4118 | 2360 | 1.1616 | 0.6672 | |
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| 0.123 | 70.0 | 2380 | 1.1671 | 0.6568 | |
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| 0.0991 | 70.5882 | 2400 | 1.1493 | 0.6587 | |
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| 0.0991 | 71.1765 | 2420 | 1.1476 | 0.6575 | |
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| 0.0991 | 71.7647 | 2440 | 1.1691 | 0.6582 | |
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| 0.0991 | 72.3529 | 2460 | 1.1867 | 0.6609 | |
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| 0.0991 | 72.9412 | 2480 | 1.1427 | 0.6519 | |
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| 0.0991 | 73.5294 | 2500 | 1.1635 | 0.6558 | |
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| 0.0991 | 74.1176 | 2520 | 1.1503 | 0.6553 | |
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| 0.0991 | 74.7059 | 2540 | 1.1487 | 0.6562 | |
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| 0.0991 | 75.2941 | 2560 | 1.1552 | 0.6576 | |
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| 0.0991 | 75.8824 | 2580 | 1.1638 | 0.6586 | |
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| 0.0991 | 76.4706 | 2600 | 1.1601 | 0.6566 | |
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| 0.0991 | 77.0588 | 2620 | 1.1603 | 0.6558 | |
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| 0.0991 | 77.6471 | 2640 | 1.1564 | 0.6547 | |
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| 0.0991 | 78.2353 | 2660 | 1.1560 | 0.6556 | |
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| 0.0991 | 78.8235 | 2680 | 1.1550 | 0.6564 | |
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| 0.0991 | 79.4118 | 2700 | 1.1550 | 0.6567 | |
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| 0.0991 | 80.0 | 2720 | 1.1550 | 0.6570 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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