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--- |
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language: |
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- vi |
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base_model: openai/whisper-tiny-vi-v1 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_11_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Tiny Vi - Anh Phuong |
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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: vi 500 |
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type: mozilla-foundation/common_voice_11_0 |
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args: 'config: hi, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 17.927542787107694 |
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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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# Whisper Tiny Vi - Anh Phuong |
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This model is a fine-tuned version of [openai/whisper-tiny-vi-v1](https://huggingface.co/openai/whisper-tiny-vi-v1) on the vi 500 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3071 |
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- Wer: 17.9275 |
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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: 1e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 4 |
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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: 500 |
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- training_steps: 4000 |
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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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| 0.4594 | 0.16 | 1000 | 0.4406 | 24.6174 | |
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| 0.3731 | 0.32 | 2000 | 0.3586 | 20.4809 | |
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| 0.3199 | 0.48 | 3000 | 0.3223 | 18.8015 | |
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| 0.3026 | 0.64 | 4000 | 0.3071 | 17.9275 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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