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--- |
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library_name: transformers |
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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 |
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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: 0.28512396694214875 |
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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 |
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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: 0.7381 |
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- Wer Ortho: 0.2850 |
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- Wer: 0.2851 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 0 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |
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|:-------------:|:-------:|:----:|:---------------:|:---------:|:------:| |
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| 0.9105 | 1.7857 | 50 | 0.6418 | 0.4115 | 0.3937 | |
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| 0.2535 | 3.5714 | 100 | 0.5773 | 0.3337 | 0.3164 | |
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| 0.0887 | 5.3571 | 150 | 0.6295 | 0.3368 | 0.3182 | |
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| 0.0288 | 7.1429 | 200 | 0.6449 | 0.3381 | 0.3211 | |
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| 0.0198 | 8.9286 | 250 | 0.6932 | 0.4170 | 0.4203 | |
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| 0.0092 | 10.7143 | 300 | 0.6835 | 0.3152 | 0.3058 | |
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| 0.0134 | 12.5 | 350 | 0.7404 | 0.3288 | 0.3264 | |
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| 0.0096 | 14.2857 | 400 | 0.7067 | 0.3374 | 0.3312 | |
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| 0.0073 | 16.0714 | 450 | 0.7303 | 0.3122 | 0.3081 | |
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| 0.0056 | 17.8571 | 500 | 0.7381 | 0.2850 | 0.2851 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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