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--- |
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language: |
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- en |
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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 |
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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: 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: 32.88075560802833 |
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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 |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the minds14 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6734 |
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- Wer Ortho: 32.6959 |
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- Wer: 32.8808 |
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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: 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: constant_with_warmup |
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- lr_scheduler_warmup_steps: 8 |
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- training_steps: 225 |
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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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| 2.8035 | 0.25 | 14 | 0.7206 | 42.1345 | 40.4368 | |
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| 0.5469 | 0.5 | 28 | 0.5327 | 36.0888 | 36.3046 | |
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| 0.4968 | 0.75 | 42 | 0.5195 | 34.7933 | 34.7107 | |
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| 0.5012 | 1.0 | 56 | 0.5551 | 33.5595 | 33.7072 | |
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| 0.1879 | 1.25 | 70 | 0.5353 | 31.5854 | 31.4640 | |
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| 0.239 | 1.5 | 84 | 0.5303 | 37.4460 | 40.6139 | |
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| 0.2082 | 1.75 | 98 | 0.5565 | 31.0302 | 31.2279 | |
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| 0.2244 | 2.0 | 112 | 0.5540 | 28.5626 | 28.6305 | |
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| 0.0679 | 2.25 | 126 | 0.5759 | 28.5009 | 28.6305 | |
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| 0.0637 | 2.5 | 140 | 0.6192 | 50.7094 | 54.0732 | |
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| 0.072 | 2.75 | 154 | 0.6093 | 31.2770 | 30.9327 | |
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| 0.0506 | 3.0 | 168 | 0.6302 | 35.2869 | 35.5372 | |
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| 0.029 | 3.25 | 182 | 0.6299 | 33.4978 | 33.5891 | |
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| 0.0405 | 3.5 | 196 | 0.6159 | 30.1049 | 30.4014 | |
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| 0.022 | 3.75 | 210 | 0.6441 | 30.7218 | 30.9917 | |
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| 0.0332 | 4.0 | 224 | 0.6734 | 32.6959 | 32.8808 | |
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### Framework versions |
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- Transformers 4.40.2 |
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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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