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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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- 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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model-index: |
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- name: wav2vec2-common_voice-tr-demo |
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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-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: 0.3856 |
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- Wer: 0.3556 |
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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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| 3.7391 | 0.92 | 100 | 3.5760 | 1.0 | |
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| 2.927 | 1.83 | 200 | 3.0796 | 0.9999 | |
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| 0.9009 | 2.75 | 300 | 0.9278 | 0.8226 | |
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| 0.6529 | 3.67 | 400 | 0.5926 | 0.6367 | |
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| 0.3623 | 4.59 | 500 | 0.5372 | 0.5692 | |
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| 0.2888 | 5.5 | 600 | 0.4407 | 0.4838 | |
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| 0.285 | 6.42 | 700 | 0.4341 | 0.4694 | |
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| 0.0842 | 7.34 | 800 | 0.4153 | 0.4302 | |
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| 0.1415 | 8.26 | 900 | 0.4317 | 0.4136 | |
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| 0.1552 | 9.17 | 1000 | 0.4145 | 0.4013 | |
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| 0.1184 | 10.09 | 1100 | 0.4115 | 0.3844 | |
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| 0.0556 | 11.01 | 1200 | 0.4182 | 0.3862 | |
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| 0.0851 | 11.93 | 1300 | 0.3985 | 0.3688 | |
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| 0.0961 | 12.84 | 1400 | 0.4030 | 0.3665 | |
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| 0.0596 | 13.76 | 1500 | 0.3880 | 0.3631 | |
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| 0.0917 | 14.68 | 1600 | 0.3878 | 0.3582 | |
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### Framework versions |
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- Transformers 4.11.0.dev0 |
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- Pytorch 1.9.0+cu111 |
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- Datasets 1.12.1 |
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- Tokenizers 0.10.3 |
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