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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- vivos |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-vivos-asr |
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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: vivos |
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type: vivos |
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config: default |
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split: None |
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args: default |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.23381058715355313 |
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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-vivos-asr |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the vivos dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3492 |
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- Wer: 0.2338 |
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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: 0.0001 |
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- train_batch_size: 32 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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: 20 |
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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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| 8.4226 | 2.0548 | 150 | 4.9423 | 1.0 | |
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| 3.59 | 4.1096 | 300 | 3.6898 | 1.0 | |
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| 3.4271 | 6.1644 | 450 | 3.5183 | 1.0 | |
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| 2.6948 | 8.2192 | 600 | 1.2770 | 0.8026 | |
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| 0.7372 | 10.2740 | 750 | 0.5197 | 0.3625 | |
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| 0.4012 | 12.3288 | 900 | 0.4108 | 0.2911 | |
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| 0.2974 | 14.3836 | 1050 | 0.3732 | 0.2604 | |
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| 0.2737 | 16.4384 | 1200 | 0.3550 | 0.2393 | |
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| 0.2108 | 18.4932 | 1350 | 0.3565 | 0.2434 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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