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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: 0.3726759841005257 |
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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/p3skrhqk) |
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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: 0.7912 |
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- Wer: 0.3727 |
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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: cosine |
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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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| 5.8168 | 2.0 | 292 | 3.6240 | 1.0 | |
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| 3.4344 | 4.0 | 584 | 3.4785 | 1.0 | |
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| 3.0271 | 6.0 | 876 | 1.8947 | 0.9142 | |
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| 1.2453 | 8.0 | 1168 | 1.0293 | 0.6091 | |
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| 0.7876 | 10.0 | 1460 | 0.8472 | 0.5229 | |
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| 0.6062 | 12.0 | 1752 | 0.7675 | 0.4748 | |
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| 0.4929 | 14.0 | 2044 | 0.7494 | 0.4303 | |
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| 0.4376 | 16.0 | 2336 | 0.7481 | 0.4063 | |
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| 0.3523 | 18.0 | 2628 | 0.7580 | 0.4007 | |
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| 0.309 | 20.0 | 2920 | 0.7676 | 0.3851 | |
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| 0.2694 | 22.0 | 3212 | 0.7631 | 0.3819 | |
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| 0.2531 | 24.0 | 3504 | 0.7717 | 0.3761 | |
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| 0.2472 | 26.0 | 3796 | 0.7825 | 0.3710 | |
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| 0.2223 | 28.0 | 4088 | 0.7905 | 0.3732 | |
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| 0.2183 | 30.0 | 4380 | 0.7912 | 0.3727 | |
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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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