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--- |
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license: cc-by-nc-4.0 |
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tags: |
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- generated_from_trainer |
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base_model: nguyenvulebinh/wav2vec2-base-vi |
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datasets: |
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- common_voice_16_1 |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-common-voice-16_1_vi |
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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: common_voice_16_1 |
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type: common_voice_16_1 |
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config: vi |
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split: None |
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args: vi |
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metrics: |
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- type: wer |
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value: 0.9998983326555511 |
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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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# wav2vec2-common-voice-16_1_vi |
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This model is a fine-tuned version of [nguyenvulebinh/wav2vec2-base-vi](https://huggingface.co/nguyenvulebinh/wav2vec2-base-vi) on the common_voice_16_1 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.5323 |
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- Wer: 0.9999 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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: 1000 |
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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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| 21.7841 | 4.2373 | 500 | 7.6684 | 0.9999 | |
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| 4.0045 | 8.4746 | 1000 | 3.5474 | 0.9999 | |
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| 3.4763 | 12.7119 | 1500 | 3.5357 | 0.9999 | |
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| 3.4721 | 16.9492 | 2000 | 3.5319 | 0.9999 | |
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| 3.4661 | 21.1864 | 2500 | 3.5321 | 0.9999 | |
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| 3.464 | 25.4237 | 3000 | 3.5315 | 0.9999 | |
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| 3.4732 | 29.6610 | 3500 | 3.5323 | 0.9999 | |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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