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--- |
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library_name: transformers |
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license: cc-by-nc-4.0 |
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base_model: nguyenvulebinh/wav2vec2-base-vi |
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tags: |
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- generated_from_trainer |
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datasets: |
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- doof-ferb/LSVSC |
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metrics: |
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- f1 |
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model-index: |
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- name: vietnamese-regional-voice-classification-model |
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results: |
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- task: |
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name: Audio Classification |
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type: audio-classification |
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dataset: |
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name: LSVSC |
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type: doof-ferb/LSVSC |
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metrics: |
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- name: F1 |
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type: f1 |
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value: 0.7852888029210245 |
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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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# vietnamese-regional-voice-classification-model |
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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 LSVSC dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6087 |
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- F1: 0.7853 |
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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: 5e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 256 |
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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_ratio: 0.1 |
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- num_epochs: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 1.0733 | 1.0 | 44 | 0.8828 | 0.7566 | |
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| 0.8621 | 2.0 | 88 | 0.7323 | 0.7653 | |
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| 0.7834 | 3.0 | 132 | 0.6746 | 0.7992 | |
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| 0.7098 | 4.0 | 176 | 0.8050 | 0.6410 | |
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| 0.6748 | 5.0 | 220 | 0.7053 | 0.7113 | |
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| 0.6335 | 6.0 | 264 | 0.6650 | 0.7491 | |
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| 0.6195 | 7.0 | 308 | 0.6096 | 0.7742 | |
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| 0.6118 | 8.0 | 352 | 0.6087 | 0.7853 | |
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### Framework versions |
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- Transformers 4.45.1 |
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- Pytorch 2.4.0 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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