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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-asr |
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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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config: default |
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split: None |
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args: default |
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metrics: |
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- type: wer |
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value: 0.46007853403141363 |
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name: Wer |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/khackho01125-CMC-University/Wav2Vec2/runs/abof73b7) |
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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: 0.9791 |
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- Wer: 0.4601 |
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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: 8e-05 |
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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: 400 |
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- num_epochs: 30 |
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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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| 6.0539 | 2.0 | 292 | 3.6334 | 1.0 | |
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| 3.4484 | 4.0 | 584 | 3.5348 | 1.0 | |
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| 3.2755 | 6.0 | 876 | 2.4805 | 0.9952 | |
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| 1.6061 | 8.0 | 1168 | 1.2597 | 0.7021 | |
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| 1.0363 | 10.0 | 1460 | 1.0996 | 0.6158 | |
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| 0.8403 | 12.0 | 1752 | 0.9858 | 0.5573 | |
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| 0.726 | 14.0 | 2044 | 0.9625 | 0.5302 | |
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| 0.6721 | 16.0 | 2336 | 0.9326 | 0.5124 | |
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| 0.5697 | 18.0 | 2628 | 0.9399 | 0.5012 | |
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| 0.5168 | 20.0 | 2920 | 0.9625 | 0.4930 | |
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| 0.4663 | 22.0 | 3212 | 0.9432 | 0.4751 | |
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| 0.4408 | 24.0 | 3504 | 0.9822 | 0.4723 | |
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| 0.4231 | 26.0 | 3796 | 0.9629 | 0.4643 | |
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| 0.3855 | 28.0 | 4088 | 0.9744 | 0.4639 | |
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| 0.3671 | 30.0 | 4380 | 0.9791 | 0.4601 | |
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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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