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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-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 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3807 |
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- Wer: 0.3456 |
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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 | 3.5932 | 1.0 | |
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| No log | 1.83 | 200 | 3.0185 | 0.9999 | |
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| No log | 2.75 | 300 | 0.9357 | 0.8007 | |
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| No log | 3.67 | 400 | 0.5945 | 0.6318 | |
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| 3.1829 | 4.59 | 500 | 0.4931 | 0.5265 | |
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| 3.1829 | 5.5 | 600 | 0.4757 | 0.4784 | |
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| 3.1829 | 6.42 | 700 | 0.4282 | 0.4540 | |
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| 3.1829 | 7.34 | 800 | 0.3995 | 0.4252 | |
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| 3.1829 | 8.26 | 900 | 0.4046 | 0.4149 | |
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| 0.2215 | 9.17 | 1000 | 0.4048 | 0.3951 | |
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| 0.2215 | 10.09 | 1100 | 0.3944 | 0.3865 | |
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| 0.2215 | 11.01 | 1200 | 0.3853 | 0.3643 | |
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| 0.2215 | 11.93 | 1300 | 0.3950 | 0.3632 | |
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| 0.2215 | 12.84 | 1400 | 0.3836 | 0.3506 | |
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| 0.1009 | 13.76 | 1500 | 0.3808 | 0.3510 | |
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| 0.1009 | 14.68 | 1600 | 0.3807 | 0.3456 | |
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### Framework versions |
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- Transformers 4.22.0.dev0 |
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- Pytorch 1.12.1+cu102 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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