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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-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: my_awesome_speach_model |
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results: [] |
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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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# my_awesome_speach_model |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2361 |
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- Accuracy: 0.6610 |
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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: 3e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- optimizer: Use adamw_torch 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_ratio: 0.1 |
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- num_epochs: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-------:|:----:|:---------------:|:--------:| |
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| No log | 0.8 | 3 | 2.1052 | 0.0847 | |
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| No log | 1.7333 | 6 | 2.0712 | 0.1610 | |
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| No log | 2.6667 | 9 | 2.0195 | 0.6356 | |
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| 2.0648 | 3.8667 | 13 | 1.9087 | 0.6864 | |
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| 2.0648 | 4.8 | 16 | 1.8101 | 0.6864 | |
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| 2.0648 | 5.7333 | 19 | 1.7046 | 0.6864 | |
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| 1.8256 | 6.6667 | 22 | 1.5664 | 0.6864 | |
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| 1.8256 | 7.8667 | 26 | 1.4010 | 0.6864 | |
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| 1.8256 | 8.8 | 29 | 1.3322 | 0.6864 | |
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| 1.4713 | 9.7333 | 32 | 1.2896 | 0.6864 | |
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| 1.4713 | 10.6667 | 35 | 1.2617 | 0.6864 | |
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| 1.4713 | 11.8667 | 39 | 1.2342 | 0.6864 | |
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| 1.307 | 12.8 | 42 | 1.2206 | 0.6864 | |
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| 1.307 | 13.7333 | 45 | 1.2094 | 0.6864 | |
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| 1.307 | 14.6667 | 48 | 1.1998 | 0.6864 | |
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| 1.2241 | 15.8667 | 52 | 1.1920 | 0.6864 | |
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| 1.2241 | 16.8 | 55 | 1.1868 | 0.6864 | |
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| 1.2241 | 17.7333 | 58 | 1.1850 | 0.6864 | |
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| 1.2053 | 18.6667 | 61 | 1.2018 | 0.6864 | |
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| 1.2053 | 19.8667 | 65 | 1.1801 | 0.6864 | |
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| 1.2053 | 20.8 | 68 | 1.1851 | 0.6864 | |
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| 1.1815 | 21.7333 | 71 | 1.1699 | 0.6864 | |
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| 1.1815 | 22.6667 | 74 | 1.1746 | 0.6864 | |
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| 1.1815 | 23.8667 | 78 | 1.2902 | 0.6864 | |
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| 1.1471 | 24.8 | 81 | 1.1601 | 0.6864 | |
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| 1.1471 | 25.7333 | 84 | 1.1527 | 0.6864 | |
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| 1.1471 | 26.6667 | 87 | 1.1841 | 0.6864 | |
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| 1.1109 | 27.8667 | 91 | 1.1406 | 0.6864 | |
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| 1.1109 | 28.8 | 94 | 1.1454 | 0.6949 | |
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| 1.1109 | 29.7333 | 97 | 1.2087 | 0.6525 | |
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| 1.0994 | 30.6667 | 100 | 1.1712 | 0.6949 | |
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| 1.0994 | 31.8667 | 104 | 1.1769 | 0.7034 | |
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| 1.0994 | 32.8 | 107 | 1.1852 | 0.6949 | |
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| 1.0516 | 33.7333 | 110 | 1.2119 | 0.6780 | |
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| 1.0516 | 34.6667 | 113 | 1.1934 | 0.6949 | |
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| 1.0516 | 35.8667 | 117 | 1.2235 | 0.6610 | |
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| 1.0547 | 36.8 | 120 | 1.1929 | 0.6780 | |
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| 1.0547 | 37.7333 | 123 | 1.1711 | 0.6780 | |
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| 1.0547 | 38.6667 | 126 | 1.1893 | 0.6864 | |
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| 0.9975 | 39.8667 | 130 | 1.1604 | 0.6864 | |
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| 0.9975 | 40.8 | 133 | 1.1802 | 0.6864 | |
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| 0.9975 | 41.7333 | 136 | 1.1613 | 0.6864 | |
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| 0.9975 | 42.6667 | 139 | 1.1852 | 0.6780 | |
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| 0.9829 | 43.8667 | 143 | 1.1511 | 0.7119 | |
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| 0.9829 | 44.8 | 146 | 1.2872 | 0.6356 | |
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| 0.9829 | 45.7333 | 149 | 1.1891 | 0.6864 | |
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| 1.0212 | 46.6667 | 152 | 1.1853 | 0.6780 | |
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| 1.0212 | 47.8667 | 156 | 1.3700 | 0.6017 | |
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| 1.0212 | 48.8 | 159 | 1.2899 | 0.6271 | |
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| 1.012 | 49.7333 | 162 | 1.2226 | 0.6695 | |
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| 1.012 | 50.6667 | 165 | 1.2168 | 0.6695 | |
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| 1.012 | 51.8667 | 169 | 1.2985 | 0.6356 | |
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| 1.0166 | 52.8 | 172 | 1.2924 | 0.6441 | |
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| 1.0166 | 53.7333 | 175 | 1.2145 | 0.6525 | |
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| 1.0166 | 54.6667 | 178 | 1.2080 | 0.6695 | |
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| 0.9709 | 55.8667 | 182 | 1.3386 | 0.6356 | |
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| 0.9709 | 56.8 | 185 | 1.2637 | 0.6610 | |
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| 0.9709 | 57.7333 | 188 | 1.1988 | 0.6949 | |
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| 0.9882 | 58.6667 | 191 | 1.2233 | 0.6610 | |
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| 0.9882 | 59.8667 | 195 | 1.3560 | 0.6441 | |
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| 0.9882 | 60.8 | 198 | 1.3280 | 0.6441 | |
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| 0.9324 | 61.7333 | 201 | 1.2938 | 0.6271 | |
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| 0.9324 | 62.6667 | 204 | 1.2439 | 0.6610 | |
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| 0.9324 | 63.8667 | 208 | 1.3100 | 0.6271 | |
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| 0.9331 | 64.8 | 211 | 1.3142 | 0.6356 | |
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| 0.9331 | 65.7333 | 214 | 1.2808 | 0.6525 | |
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| 0.9331 | 66.6667 | 217 | 1.2599 | 0.6525 | |
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| 0.9155 | 67.8667 | 221 | 1.2801 | 0.6525 | |
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| 0.9155 | 68.8 | 224 | 1.2173 | 0.6864 | |
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| 0.9155 | 69.7333 | 227 | 1.2677 | 0.6525 | |
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| 0.88 | 70.6667 | 230 | 1.2324 | 0.6780 | |
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| 0.88 | 71.8667 | 234 | 1.1966 | 0.6780 | |
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| 0.88 | 72.8 | 237 | 1.2495 | 0.6695 | |
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| 0.9119 | 73.7333 | 240 | 1.2212 | 0.6695 | |
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| 0.9119 | 74.6667 | 243 | 1.2157 | 0.6695 | |
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| 0.9119 | 75.8667 | 247 | 1.2324 | 0.6610 | |
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| 0.8721 | 76.8 | 250 | 1.2343 | 0.6695 | |
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| 0.8721 | 77.7333 | 253 | 1.2306 | 0.6610 | |
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| 0.8721 | 78.6667 | 256 | 1.2322 | 0.6610 | |
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| 0.8741 | 79.8667 | 260 | 1.2413 | 0.6695 | |
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| 0.8741 | 80.8 | 263 | 1.2184 | 0.6949 | |
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| 0.8741 | 81.7333 | 266 | 1.2102 | 0.6864 | |
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| 0.8741 | 82.6667 | 269 | 1.2311 | 0.6780 | |
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| 0.8509 | 83.8667 | 273 | 1.2596 | 0.6525 | |
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| 0.8509 | 84.8 | 276 | 1.2589 | 0.6525 | |
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| 0.8509 | 85.7333 | 279 | 1.2425 | 0.6695 | |
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| 0.8614 | 86.6667 | 282 | 1.2361 | 0.6695 | |
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| 0.8614 | 87.8667 | 286 | 1.2317 | 0.6695 | |
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| 0.8614 | 88.8 | 289 | 1.2295 | 0.6695 | |
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| 0.8762 | 89.7333 | 292 | 1.2310 | 0.6695 | |
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| 0.8762 | 90.6667 | 295 | 1.2352 | 0.6695 | |
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| 0.8762 | 91.8667 | 299 | 1.2362 | 0.6610 | |
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| 0.8594 | 92.2667 | 300 | 1.2361 | 0.6610 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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