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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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- generated_from_trainer |
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datasets: |
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- PolyAI/minds14 |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-tiny-en-US |
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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: PolyAI/minds14 |
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type: PolyAI/minds14 |
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config: en-US |
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split: train |
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args: en-US |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.296010296010296 |
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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-en-US |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4990 |
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- Wer Ortho: 0.2965 |
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- Wer: 0.2960 |
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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-07 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: constant_with_warmup |
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- lr_scheduler_warmup_steps: 100 |
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- training_steps: 500 |
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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 Ortho | Wer | |
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|:-------------:|:------:|:----:|:---------------:|:---------:|:------:| |
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| 0.0244 | 0.8969 | 50 | 0.5282 | 0.3012 | 0.3005 | |
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| 0.0178 | 1.7937 | 100 | 0.5213 | 0.2985 | 0.2986 | |
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| 0.0171 | 2.6906 | 150 | 0.5147 | 0.2979 | 0.2967 | |
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| 0.0121 | 3.5874 | 200 | 0.5092 | 0.2925 | 0.2915 | |
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| 0.0071 | 4.4843 | 250 | 0.5057 | 0.3072 | 0.3069 | |
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| 0.0073 | 5.3812 | 300 | 0.5034 | 0.2945 | 0.2941 | |
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| 0.003 | 6.2780 | 350 | 0.5014 | 0.2945 | 0.2934 | |
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| 0.0036 | 7.1749 | 400 | 0.5003 | 0.2972 | 0.2967 | |
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| 0.0034 | 8.0717 | 450 | 0.4997 | 0.2965 | 0.2960 | |
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| 0.0034 | 8.9686 | 500 | 0.4990 | 0.2965 | 0.2960 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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