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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-minds14-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: 0.35400516795865633 |
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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-minds14-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: 0.7195 |
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- Wer Ortho: 0.3560 |
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- Wer: 0.3540 |
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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: 16 |
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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: 50 |
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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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| 1.8452 | 1.79 | 50 | 0.8160 | 0.3890 | 0.3534 | |
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| 0.3172 | 3.57 | 100 | 0.5341 | 0.3573 | 0.3547 | |
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| 0.1191 | 5.36 | 150 | 0.5525 | 0.3284 | 0.3217 | |
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| 0.0363 | 7.14 | 200 | 0.6061 | 0.3472 | 0.3456 | |
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| 0.0099 | 8.93 | 250 | 0.6240 | 0.3546 | 0.3540 | |
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| 0.0036 | 10.71 | 300 | 0.6596 | 0.3560 | 0.3527 | |
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| 0.0019 | 12.5 | 350 | 0.6777 | 0.3513 | 0.3508 | |
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| 0.0012 | 14.29 | 400 | 0.6946 | 0.3540 | 0.3527 | |
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| 0.0009 | 16.07 | 450 | 0.7079 | 0.3526 | 0.3514 | |
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| 0.0007 | 17.86 | 500 | 0.7195 | 0.3560 | 0.3540 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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