End of training
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README.md
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---
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base_model: facebook/wav2vec2-base
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datasets:
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- vivos
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license: apache-2.0
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metrics:
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- wer
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tags:
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- generated_from_trainer
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model-index:
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- name: wav2vec2-vivos
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results:
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- task:
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type: automatic-speech-recognition
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name: Automatic Speech Recognition
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dataset:
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name: vivos
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type: vivos
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split: None
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args: default
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metrics:
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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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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.
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- Wer: 0.
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## Model description
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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:
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- lr_scheduler_warmup_ratio: 0.
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- num_epochs: 20
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- mixed_precision_training: Native AMP
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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### Framework versions
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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
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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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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: 0.23636599442318915
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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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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: 0.4755
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- Wer: 0.2364
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## Model description
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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_ratio: 0.2
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- num_epochs: 20
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- mixed_precision_training: Native AMP
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| 1.349 | 2.0 | 146 | 0.9904 | 0.6088 |
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| 0.718 | 4.0 | 292 | 0.6959 | 0.4630 |
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| 0.4692 | 6.0 | 438 | 0.5304 | 0.3414 |
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| 0.3385 | 8.0 | 584 | 0.5078 | 0.3216 |
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| 0.2627 | 10.0 | 730 | 0.4659 | 0.2788 |
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| 0.2033 | 12.0 | 876 | 0.4751 | 0.2656 |
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| 0.1699 | 14.0 | 1022 | 0.4659 | 0.2519 |
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| 0.1688 | 16.0 | 1168 | 0.4662 | 0.2394 |
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| 0.1269 | 18.0 | 1314 | 0.4707 | 0.2375 |
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| 0.1162 | 20.0 | 1460 | 0.4755 | 0.2364 |
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### Framework versions
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