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--- |
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library_name: transformers |
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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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- audiofolder |
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metrics: |
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- wer |
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model-index: |
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- name: w2v2-lmk_augmented |
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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: audiofolder |
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type: audiofolder |
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config: default |
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split: test |
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args: default |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.4878048780487805 |
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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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# w2v2-lmk_augmented |
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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 audiofolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2406 |
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- Wer: 0.4878 |
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- Cer: 0.1858 |
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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: 0.0001 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 300 |
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- num_epochs: 100 |
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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 | Cer | |
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|:-------------:|:-------:|:----:|:---------------:|:------:|:------:| |
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| 8.5498 | 2.7123 | 100 | 4.0528 | 1.0 | 1.0 | |
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| 3.1716 | 5.4110 | 200 | 2.9634 | 1.0 | 1.0 | |
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| 2.9756 | 8.1096 | 300 | 2.8924 | 1.0 | 1.0 | |
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| 2.8279 | 10.8219 | 400 | 2.5968 | 1.0 | 1.0 | |
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| 2.2866 | 13.5205 | 500 | 1.7827 | 0.9895 | 0.6283 | |
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| 1.619 | 16.2192 | 600 | 1.3242 | 0.9443 | 0.4021 | |
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| 1.2926 | 18.9315 | 700 | 1.1299 | 0.7875 | 0.2833 | |
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| 1.0181 | 21.6301 | 800 | 1.1390 | 0.6585 | 0.2513 | |
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| 0.8774 | 24.3288 | 900 | 1.0760 | 0.6132 | 0.2338 | |
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| 0.7471 | 27.0274 | 1000 | 0.9959 | 0.5889 | 0.2155 | |
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| 0.6542 | 29.7397 | 1100 | 1.0575 | 0.5575 | 0.2117 | |
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| 0.5632 | 32.4384 | 1200 | 1.0240 | 0.5784 | 0.2171 | |
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| 0.4834 | 35.1370 | 1300 | 1.0971 | 0.5505 | 0.1912 | |
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| 0.4716 | 37.8493 | 1400 | 1.1336 | 0.5749 | 0.2056 | |
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| 0.45 | 40.5479 | 1500 | 1.0703 | 0.5679 | 0.2079 | |
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| 0.394 | 43.2466 | 1600 | 1.1579 | 0.5645 | 0.2178 | |
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| 0.3588 | 45.9589 | 1700 | 1.0555 | 0.5296 | 0.1896 | |
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| 0.3217 | 48.6575 | 1800 | 1.2323 | 0.5575 | 0.2102 | |
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| 0.3245 | 51.3562 | 1900 | 1.1639 | 0.5401 | 0.2018 | |
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| 0.289 | 54.0548 | 2000 | 1.1304 | 0.5122 | 0.1927 | |
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| 0.28 | 56.7671 | 2100 | 1.2295 | 0.5296 | 0.2003 | |
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| 0.2521 | 59.4658 | 2200 | 1.1612 | 0.5226 | 0.1950 | |
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| 0.2624 | 62.1644 | 2300 | 1.1982 | 0.5157 | 0.2003 | |
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| 0.2402 | 64.8767 | 2400 | 1.2075 | 0.5296 | 0.1988 | |
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| 0.2258 | 67.5753 | 2500 | 1.2091 | 0.5366 | 0.2003 | |
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| 0.2232 | 70.2740 | 2600 | 1.1830 | 0.5296 | 0.1957 | |
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| 0.2181 | 72.9863 | 2700 | 1.2001 | 0.5157 | 0.1942 | |
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| 0.2214 | 75.6849 | 2800 | 1.1942 | 0.5052 | 0.1889 | |
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| 0.1752 | 78.3836 | 2900 | 1.1873 | 0.5087 | 0.1896 | |
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| 0.1891 | 81.0822 | 3000 | 1.2159 | 0.5192 | 0.1927 | |
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| 0.1733 | 83.7945 | 3100 | 1.2105 | 0.5017 | 0.1881 | |
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| 0.1982 | 86.4932 | 3200 | 1.2331 | 0.5087 | 0.1874 | |
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| 0.1681 | 89.1918 | 3300 | 1.1848 | 0.4808 | 0.1790 | |
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| 0.1631 | 91.9041 | 3400 | 1.2273 | 0.4878 | 0.1858 | |
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| 0.1579 | 94.6027 | 3500 | 1.2334 | 0.4948 | 0.1843 | |
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| 0.1795 | 97.3014 | 3600 | 1.2399 | 0.4878 | 0.1851 | |
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| 0.1592 | 100.0 | 3700 | 1.2406 | 0.4878 | 0.1858 | |
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### Framework versions |
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- Transformers 4.57.1 |
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- Pytorch 2.8.0+cu128 |
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- Datasets 3.0.0 |
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- Tokenizers 0.22.1 |
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