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- library_name: transformers
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  ---
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+ license: cc-by-nc-4.0
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+ base_model: nguyenvulebinh/wav2vec2-base-vietnamese-250h
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+ tags:
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+ - generated_from_trainer
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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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+ name: Automatic Speech Recognition
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+ type: 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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+ - name: Wer
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+ type: wer
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+ value: 1.0
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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: 4.9208
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+ - Wer: 1.0
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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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+ | 14.5388 | 4.3103 | 500 | 4.6367 | 1.0 |
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+ | 4.7736 | 8.6207 | 1000 | 4.6004 | 1.0 |
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+ | 4.0887 | 12.9310 | 1500 | 4.5495 | 1.0 |
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+ | 3.8825 | 17.2414 | 2000 | 4.3716 | 1.0 |
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+ | 3.7765 | 21.5517 | 2500 | 4.8458 | 1.0 |
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+ | 3.6492 | 25.8621 | 3000 | 4.9208 | 1.0 |
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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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