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--- |
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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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model-index: |
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- name: wav2vec2-large-xls-r-300m-ipa |
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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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# wav2vec2-large-xls-r-300m-ipa |
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This model was trained from scratch 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: 0.7309 |
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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: 6 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 24 |
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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: 240 |
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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 | |
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|:-------------:|:--------:|:-----:|:---------------:| |
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| 0.1677 | 3.6866 | 200 | 1.0381 | |
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| 0.1214 | 7.3733 | 400 | 0.5607 | |
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| 0.1272 | 11.0599 | 600 | 0.5442 | |
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| 0.135 | 14.7465 | 800 | 0.5933 | |
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| 0.0824 | 18.4332 | 1000 | 0.6316 | |
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| 0.0711 | 22.1198 | 1200 | 0.5971 | |
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| 0.0653 | 25.8065 | 1400 | 0.6050 | |
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| 0.0499 | 29.4931 | 1600 | 0.6699 | |
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| 0.0516 | 33.1797 | 1800 | 0.6940 | |
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| 0.0507 | 36.8664 | 2000 | 0.7045 | |
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| 0.0478 | 40.5530 | 2200 | 0.7603 | |
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| 0.045 | 44.2396 | 2400 | 0.7415 | |
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| 0.0419 | 47.9263 | 2600 | 0.7341 | |
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| 0.0344 | 51.6129 | 2800 | 0.7328 | |
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| 0.0354 | 55.2995 | 3000 | 0.8550 | |
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| 0.0268 | 58.9862 | 3200 | 0.7838 | |
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| 0.0383 | 62.6728 | 3400 | 0.7995 | |
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| 0.0371 | 66.3594 | 3600 | 0.7765 | |
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| 0.0264 | 70.0461 | 3800 | 0.8186 | |
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| 0.0212 | 73.7327 | 4000 | 0.7439 | |
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| 0.0177 | 77.4194 | 4200 | 0.7830 | |
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| 0.0204 | 81.1060 | 4400 | 0.8145 | |
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| 0.0254 | 84.7926 | 4600 | 0.8149 | |
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| 0.0257 | 88.4793 | 4800 | 0.7663 | |
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| 0.0126 | 92.1659 | 5000 | 0.7704 | |
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| 0.0196 | 95.8525 | 5200 | 0.7660 | |
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| 0.0185 | 99.5392 | 5400 | 0.8580 | |
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| 0.0236 | 103.2258 | 5600 | 0.8169 | |
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| 0.0141 | 106.9124 | 5800 | 0.8222 | |
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| 0.0142 | 110.5991 | 6000 | 0.9001 | |
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| 0.0098 | 114.2857 | 6200 | 0.8509 | |
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| 0.0372 | 117.9724 | 6400 | 0.7734 | |
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| 0.0075 | 121.6590 | 6600 | 0.8911 | |
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| 0.0118 | 125.3456 | 6800 | 0.8347 | |
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| 0.0115 | 129.0323 | 7000 | 0.8926 | |
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| 0.0164 | 132.7189 | 7200 | 0.7985 | |
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| 0.006 | 136.4055 | 7400 | 0.7571 | |
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| 0.0124 | 140.0922 | 7600 | 0.8476 | |
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| 0.0141 | 143.7788 | 7800 | 0.8071 | |
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| 0.0065 | 147.4654 | 8000 | 0.7630 | |
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| 0.0095 | 151.1521 | 8200 | 0.7161 | |
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| 0.0063 | 154.8387 | 8400 | 0.8165 | |
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| 0.0107 | 158.5253 | 8600 | 0.7411 | |
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| 0.0037 | 162.2120 | 8800 | 0.7424 | |
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| 0.0045 | 165.8986 | 9000 | 0.7611 | |
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| 0.0044 | 169.5853 | 9200 | 0.7278 | |
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| 0.0043 | 173.2719 | 9400 | 0.7396 | |
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| 0.0025 | 176.9585 | 9600 | 0.7215 | |
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| 0.0029 | 180.6452 | 9800 | 0.7551 | |
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| 0.0067 | 184.3318 | 10000 | 0.7518 | |
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| 0.0062 | 188.0184 | 10200 | 0.7668 | |
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| 0.0065 | 191.7051 | 10400 | 0.7433 | |
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| 0.0024 | 195.3917 | 10600 | 0.7942 | |
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| 0.0039 | 199.0783 | 10800 | 0.7448 | |
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| 0.0024 | 202.7650 | 11000 | 0.7290 | |
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| 0.0036 | 206.4516 | 11200 | 0.7678 | |
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| 0.0001 | 210.1382 | 11400 | 0.7390 | |
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| 0.0009 | 213.8249 | 11600 | 0.7292 | |
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| 0.0008 | 217.5115 | 11800 | 0.7383 | |
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| 0.0009 | 221.1982 | 12000 | 0.7435 | |
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| 0.0009 | 224.8848 | 12200 | 0.7324 | |
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| 0.0007 | 228.5714 | 12400 | 0.7444 | |
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| 0.0002 | 232.2581 | 12600 | 0.7228 | |
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| 0.0005 | 235.9447 | 12800 | 0.7309 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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