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--- |
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language: |
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- tr |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- common_voice |
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- generated_from_trainer |
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datasets: |
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- common_voice |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-common_voice-tr-demo |
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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: COMMON_VOICE - TR |
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type: common_voice |
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config: tr |
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split: test |
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args: 'Config: tr, Training split: train+validation, Eval split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.3446021856807272 |
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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-common_voice-tr-demo |
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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 - TR dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3794 |
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- Wer: 0.3446 |
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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: 15.0 |
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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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| No log | 0.92 | 100 | 3.5956 | 1.0 | |
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| No log | 1.83 | 200 | 3.0269 | 0.9999 | |
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| No log | 2.75 | 300 | 0.9827 | 0.8111 | |
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| No log | 3.67 | 400 | 0.6236 | 0.6304 | |
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| 3.1866 | 4.59 | 500 | 0.5016 | 0.5264 | |
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| 3.1866 | 5.5 | 600 | 0.4523 | 0.4935 | |
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| 3.1866 | 6.42 | 700 | 0.4306 | 0.4528 | |
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| 3.1866 | 7.34 | 800 | 0.4328 | 0.4329 | |
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| 3.1866 | 8.26 | 900 | 0.4026 | 0.4105 | |
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| 0.227 | 9.17 | 1000 | 0.4096 | 0.4080 | |
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| 0.227 | 10.09 | 1100 | 0.3921 | 0.3915 | |
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| 0.227 | 11.01 | 1200 | 0.3830 | 0.3778 | |
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| 0.227 | 11.93 | 1300 | 0.3846 | 0.3616 | |
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| 0.227 | 12.84 | 1400 | 0.3888 | 0.3619 | |
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| 0.1046 | 13.76 | 1500 | 0.3861 | 0.3509 | |
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| 0.1046 | 14.68 | 1600 | 0.3798 | 0.3455 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.12.0+cu116 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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