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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: working |
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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: 0.4125911199469848 |
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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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# working |
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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: 0.7102 |
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- Wer: 0.4126 |
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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: 2 |
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- total_train_batch_size: 64 |
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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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| 6.3485 | 2.0 | 292 | 3.7183 | 1.0 | |
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| 3.4479 | 4.0 | 584 | 3.5977 | 1.0 | |
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| 2.948 | 6.0 | 876 | 1.7093 | 0.8420 | |
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| 1.2556 | 8.0 | 1168 | 1.0140 | 0.5846 | |
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| 0.9216 | 10.0 | 1460 | 0.8558 | 0.5142 | |
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| 0.7769 | 12.0 | 1752 | 0.7731 | 0.4643 | |
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| 0.6968 | 14.0 | 2044 | 0.7458 | 0.4394 | |
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| 0.6813 | 16.0 | 2336 | 0.7549 | 0.4385 | |
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| 0.5996 | 18.0 | 2628 | 0.7186 | 0.4128 | |
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| 0.572 | 20.0 | 2920 | 0.7102 | 0.4126 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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