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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-vietnamese-250h |
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datasets: |
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- common_voice_17_0 |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-common-voice-17_0_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_17_0 |
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type: common_voice_17_0 |
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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: 0.43487928843710294 |
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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-17_0_vi |
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This model is a fine-tuned version of [nguyenvulebinh/wav2vec2-base-vietnamese-250h](https://huggingface.co/nguyenvulebinh/wav2vec2-base-vietnamese-250h) on the common_voice_17_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7992 |
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- Wer: 0.4349 |
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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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| 0.261 | 4.3103 | 500 | 0.4182 | 0.3492 | |
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| 0.2061 | 8.6207 | 1000 | 0.5416 | 0.4044 | |
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| 0.1883 | 12.9310 | 1500 | 0.6796 | 0.4304 | |
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| 0.1336 | 17.2414 | 2000 | 0.8089 | 0.4378 | |
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| 0.1257 | 21.5517 | 2500 | 0.8244 | 0.4426 | |
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| 0.098 | 25.8621 | 3000 | 0.7992 | 0.4349 | |
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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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