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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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- robust-speech-event |
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datasets: |
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- common_voice |
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model-index: |
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- name: wav2vec2-large-xlsr-53-W2V2-TR-MED |
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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-xlsr-53-W2V2-TR-MED |
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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: 0.4467 |
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- Wer: 0.4598 |
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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: 60 |
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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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| 5.1343 | 4.21 | 400 | 2.3674 | 1.0372 | |
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| 0.8075 | 8.42 | 800 | 0.4583 | 0.6308 | |
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| 0.3209 | 12.63 | 1200 | 0.4291 | 0.5531 | |
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| 0.2273 | 16.84 | 1600 | 0.4348 | 0.5378 | |
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| 0.1764 | 21.05 | 2000 | 0.4550 | 0.5326 | |
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| 0.148 | 25.26 | 2400 | 0.4839 | 0.5319 | |
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| 0.1268 | 29.47 | 2800 | 0.4515 | 0.5070 | |
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| 0.1113 | 33.68 | 3200 | 0.4590 | 0.4930 | |
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| 0.1025 | 37.89 | 3600 | 0.4546 | 0.4888 | |
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| 0.0922 | 42.11 | 4000 | 0.4782 | 0.4852 | |
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| 0.082 | 46.32 | 4400 | 0.4605 | 0.4752 | |
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| 0.0751 | 50.53 | 4800 | 0.4358 | 0.4689 | |
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| 0.0699 | 54.74 | 5200 | 0.4359 | 0.4629 | |
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| 0.0633 | 58.95 | 5600 | 0.4467 | 0.4598 | |
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### Framework versions |
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- Transformers 4.11.3 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.14.0 |
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- Tokenizers 0.10.3 |
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