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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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- minds14 |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-tiny-finetune-en |
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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: 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: 0.2982021078735276 |
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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-finetune-en |
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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: 0.5945 |
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- Wer Ortho: 0.2999 |
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- Wer: 0.2982 |
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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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- num_epochs: 5 |
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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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| 0.4669 | 0.8929 | 25 | 0.5975 | 0.3205 | 0.3187 | |
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| 0.3668 | 1.7857 | 50 | 0.5618 | 0.3044 | 0.3025 | |
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| 0.3007 | 2.6786 | 75 | 0.5626 | 0.2967 | 0.2957 | |
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| 0.1878 | 3.5714 | 100 | 0.5755 | 0.3096 | 0.3094 | |
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| 0.1429 | 4.4643 | 125 | 0.5945 | 0.2999 | 0.2982 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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