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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice |
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model-index: |
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- name: wav2vec2-large-xls-r-53h-turkish-colab |
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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-53h-turkish-colab |
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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 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4135 |
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- Wer: 0.3247 |
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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: 16 |
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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: 32 |
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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: 32 |
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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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| 9.4875 | 0.92 | 100 | 3.5328 | 1.0 | |
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| 3.1866 | 1.83 | 200 | 3.0955 | 1.0 | |
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| 2.027 | 2.75 | 300 | 0.9002 | 0.7685 | |
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| 0.7285 | 3.67 | 400 | 0.6279 | 0.6693 | |
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| 0.4693 | 4.59 | 500 | 0.5672 | 0.5643 | |
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| 0.3615 | 5.5 | 600 | 0.4995 | 0.5094 | |
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| 0.2846 | 6.42 | 700 | 0.4561 | 0.4797 | |
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| 0.2253 | 7.34 | 800 | 0.4742 | 0.4675 | |
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| 0.2004 | 8.26 | 900 | 0.4462 | 0.4345 | |
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| 0.173 | 9.17 | 1000 | 0.4688 | 0.4333 | |
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| 0.1547 | 10.09 | 1100 | 0.4429 | 0.4206 | |
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| 0.1444 | 11.01 | 1200 | 0.4662 | 0.4144 | |
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| 0.1274 | 11.93 | 1300 | 0.4675 | 0.4213 | |
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| 0.1164 | 12.84 | 1400 | 0.4947 | 0.4073 | |
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| 0.1081 | 13.76 | 1500 | 0.4223 | 0.3915 | |
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| 0.1025 | 14.68 | 1600 | 0.4493 | 0.3912 | |
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| 0.0944 | 15.6 | 1700 | 0.4527 | 0.3848 | |
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| 0.0943 | 16.51 | 1800 | 0.4288 | 0.3810 | |
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| 0.0885 | 17.43 | 1900 | 0.4313 | 0.3670 | |
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| 0.0781 | 18.35 | 2000 | 0.4729 | 0.3790 | |
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| 0.0828 | 19.27 | 2100 | 0.4560 | 0.3651 | |
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| 0.0753 | 20.18 | 2200 | 0.4478 | 0.3599 | |
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| 0.0702 | 21.1 | 2300 | 0.4518 | 0.3595 | |
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| 0.0666 | 22.02 | 2400 | 0.4080 | 0.3489 | |
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| 0.0661 | 22.94 | 2500 | 0.4414 | 0.3507 | |
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| 0.0607 | 23.85 | 2600 | 0.4209 | 0.3538 | |
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| 0.058 | 24.77 | 2700 | 0.4302 | 0.3382 | |
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| 0.0596 | 25.69 | 2800 | 0.3939 | 0.3328 | |
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| 0.052 | 26.61 | 2900 | 0.4374 | 0.3311 | |
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| 0.0473 | 27.52 | 3000 | 0.4406 | 0.3363 | |
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| 0.0483 | 28.44 | 3100 | 0.4272 | 0.3286 | |
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| 0.049 | 29.36 | 3200 | 0.4189 | 0.3257 | |
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| 0.0433 | 30.28 | 3300 | 0.4242 | 0.3229 | |
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| 0.0438 | 31.19 | 3400 | 0.4135 | 0.3247 | |
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### Framework versions |
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- Transformers 4.11.3 |
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- Pytorch 1.10.0+cu113 |
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- Datasets 1.18.3 |
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- Tokenizers 0.10.3 |
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