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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-large |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: wav2vec2-turkish-tr-voice |
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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-turkish-tr-voice |
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This model is a fine-tuned version of [facebook/wav2vec2-large](https://huggingface.co/facebook/wav2vec2-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0239 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- total_train_batch_size: 8 |
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- total_eval_batch_size: 8 |
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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: 1000 |
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- num_epochs: 50 |
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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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| 2.479 | 0.0765 | 1000 | 0.2672 | |
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| 0.3629 | 0.1531 | 2000 | 0.1266 | |
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| 0.2485 | 0.2296 | 3000 | 0.1020 | |
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| 0.2082 | 0.3062 | 4000 | 0.0916 | |
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| 0.1913 | 0.3827 | 5000 | 0.0737 | |
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| 0.1757 | 0.4593 | 6000 | 0.0741 | |
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| 0.1638 | 0.5358 | 7000 | 0.0686 | |
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| 0.1567 | 0.6124 | 8000 | 0.0636 | |
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| 0.153 | 0.6889 | 9000 | 0.0608 | |
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| 0.1488 | 0.7655 | 10000 | 0.0583 | |
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| 0.1374 | 0.8420 | 11000 | 0.0536 | |
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| 0.1357 | 0.9186 | 12000 | 0.0511 | |
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| 0.1393 | 0.9951 | 13000 | 0.0525 | |
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| 0.1314 | 1.0716 | 14000 | 0.0491 | |
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| 0.1194 | 1.1482 | 15000 | 0.0498 | |
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| 0.1277 | 1.2247 | 16000 | 0.0484 | |
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| 0.1173 | 1.3013 | 17000 | 0.0443 | |
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| 0.1214 | 1.3778 | 18000 | 0.0443 | |
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| 0.1136 | 1.4544 | 19000 | 0.0453 | |
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| 0.1107 | 1.5309 | 20000 | 0.0444 | |
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| 0.1155 | 1.6075 | 21000 | 0.0419 | |
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| 0.1102 | 1.6840 | 22000 | 0.0406 | |
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| 0.107 | 1.7606 | 23000 | 0.0414 | |
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| 0.104 | 1.8371 | 24000 | 0.0397 | |
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| 0.1095 | 1.9137 | 25000 | 0.0405 | |
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| 0.1004 | 1.9902 | 26000 | 0.0370 | |
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| 0.1038 | 2.0667 | 27000 | 0.0394 | |
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| 0.097 | 2.1433 | 28000 | 0.0422 | |
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| 0.0983 | 2.2198 | 29000 | 0.0369 | |
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| 0.0953 | 2.2964 | 30000 | 0.0405 | |
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| 0.0958 | 2.3729 | 31000 | 0.0362 | |
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| 0.0934 | 2.4495 | 32000 | 0.0376 | |
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| 0.0939 | 2.5260 | 33000 | 0.0348 | |
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| 0.0909 | 2.6026 | 34000 | 0.0356 | |
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| 0.0927 | 2.6791 | 35000 | 0.0332 | |
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| 0.0915 | 2.7557 | 36000 | 0.0324 | |
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| 0.0933 | 2.8322 | 37000 | 0.0354 | |
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| 0.0905 | 2.9088 | 38000 | 0.0328 | |
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| 0.0905 | 2.9853 | 39000 | 0.0351 | |
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| 0.0869 | 3.0618 | 40000 | 0.0303 | |
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| 0.0869 | 3.1384 | 41000 | 0.0351 | |
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| 0.0877 | 3.2149 | 42000 | 0.0339 | |
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| 0.0859 | 3.2915 | 43000 | 0.0342 | |
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| 0.0922 | 3.3680 | 44000 | 0.0331 | |
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| 0.0848 | 3.4446 | 45000 | 0.0350 | |
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| 0.0836 | 3.5211 | 46000 | 0.0307 | |
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| 0.0887 | 3.5977 | 47000 | 0.0317 | |
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| 0.088 | 3.6742 | 48000 | 0.0298 | |
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| 0.083 | 3.7508 | 49000 | 0.0325 | |
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| 0.0824 | 3.8273 | 50000 | 0.0318 | |
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| 0.0811 | 3.9039 | 51000 | 0.0315 | |
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| 0.0797 | 3.9804 | 52000 | 0.0289 | |
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| 0.0794 | 4.0570 | 53000 | 0.0330 | |
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| 0.0844 | 4.1335 | 54000 | 0.0325 | |
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| 0.0784 | 4.2100 | 55000 | 0.0330 | |
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| 0.0765 | 4.2866 | 56000 | 0.0295 | |
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| 0.0793 | 4.3631 | 57000 | 0.0293 | |
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| 0.0775 | 4.4397 | 58000 | 0.0302 | |
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| 0.076 | 4.5162 | 59000 | 0.0283 | |
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| 0.074 | 4.5928 | 60000 | 0.0277 | |
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| 0.0766 | 4.6693 | 61000 | 0.0296 | |
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| 0.074 | 4.7459 | 62000 | 0.0274 | |
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| 0.0744 | 4.8224 | 63000 | 0.0276 | |
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| 0.0784 | 4.8990 | 64000 | 0.0295 | |
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| 0.0763 | 4.9755 | 65000 | 0.0277 | |
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| 0.0722 | 5.0521 | 66000 | 0.0290 | |
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| 0.0713 | 5.1286 | 67000 | 0.0277 | |
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| 0.0708 | 5.2051 | 68000 | 0.0308 | |
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| 0.0714 | 5.2817 | 69000 | 0.0300 | |
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| 0.0742 | 5.3582 | 70000 | 0.0273 | |
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| 0.0717 | 5.4348 | 71000 | 0.0261 | |
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| 0.0699 | 5.5113 | 72000 | 0.0277 | |
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| 0.0695 | 5.5879 | 73000 | 0.0275 | |
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| 0.0686 | 5.6644 | 74000 | 0.0267 | |
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| 0.0702 | 5.7410 | 75000 | 0.0272 | |
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| 0.0672 | 5.8175 | 76000 | 0.0269 | |
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| 0.0724 | 5.8941 | 77000 | 0.0274 | |
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| 0.0696 | 5.9706 | 78000 | 0.0246 | |
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| 0.07 | 6.0472 | 79000 | 0.0325 | |
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| 0.0903 | 6.1237 | 80000 | 0.0276 | |
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| 0.0693 | 6.2002 | 81000 | 0.0250 | |
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| 0.0714 | 6.2768 | 82000 | 0.0255 | |
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| 0.0655 | 6.3533 | 83000 | 0.0258 | |
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| 0.0652 | 6.4299 | 84000 | 0.0270 | |
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| 0.0709 | 6.5064 | 85000 | 0.0253 | |
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| 0.0666 | 6.5830 | 86000 | 0.0253 | |
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| 0.0678 | 6.6595 | 87000 | 0.0257 | |
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| 0.0692 | 6.7361 | 88000 | 0.0236 | |
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| 0.0657 | 6.8126 | 89000 | 0.0287 | |
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| 0.0657 | 6.8892 | 90000 | 0.0240 | |
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| 0.0646 | 6.9657 | 91000 | 0.0245 | |
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| 0.0616 | 7.0423 | 92000 | 0.0254 | |
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| 0.0653 | 7.1188 | 93000 | 0.0291 | |
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| 0.0653 | 7.1953 | 94000 | 0.0253 | |
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| 0.0617 | 7.2719 | 95000 | 0.0239 | |
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| 0.0616 | 7.3484 | 96000 | 0.0245 | |
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| 0.0661 | 7.4250 | 97000 | 0.0237 | |
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| 0.0629 | 7.5015 | 98000 | 0.0239 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.19.1 |
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