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--- |
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license: apache-2.0 |
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base_model: openai/whisper-tiny |
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tags: |
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- whisper-event |
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- generated_from_trainer |
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datasets: |
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- 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: WhisperTinyFinnishV3 |
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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_11_0 |
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type: common_voice_11_0 |
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config: fi |
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split: test |
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args: fi |
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metrics: |
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- name: Wer |
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type: wer |
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value: 45.13758009800226 |
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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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# WhisperTinyFinnishV3 |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the common_voice_11_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5363 |
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- Wer: 45.1376 |
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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: 3e-06 |
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- train_batch_size: 32 |
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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: 1000 |
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- training_steps: 10000 |
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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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| 0.9236 | 0.1 | 1000 | 0.7783 | 58.5187 | |
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| 0.727 | 0.2 | 2000 | 0.6638 | 53.1097 | |
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| 0.6867 | 0.3 | 3000 | 0.6113 | 50.2639 | |
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| 0.8348 | 0.4 | 4000 | 0.5882 | 48.2661 | |
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| 0.5165 | 0.5 | 5000 | 0.5679 | 47.1259 | |
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| 0.5509 | 0.6 | 6000 | 0.5540 | 46.6359 | |
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| 0.639 | 0.7 | 7000 | 0.5466 | 46.5228 | |
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| 0.4715 | 0.8 | 8000 | 0.5400 | 45.9763 | |
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| 0.6306 | 0.9 | 9000 | 0.5363 | 45.1376 | |
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| 0.4598 | 1.0 | 10000 | 0.5352 | 45.4768 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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