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--- |
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license: apache-2.0 |
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base_model: openai/whisper-small |
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tags: |
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- generated_from_trainer |
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datasets: |
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- librispeech-clean |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small English 1h |
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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: Librispeech |
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type: librispeech-clean |
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config: default |
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split: None |
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args: 'config: english, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 53.45675203126608 |
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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 Small English 1h |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Librispeech dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8110 |
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- Wer: 53.4568 |
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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-07 |
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- train_batch_size: 16 |
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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: linear |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 1000 |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:| |
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| 0.0582 | 10.0 | 200 | 1.8847 | 56.4620 | |
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| 0.0495 | 20.0 | 400 | 1.8598 | 55.1579 | |
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| 0.042 | 30.0 | 600 | 1.8303 | 54.2240 | |
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| 0.0309 | 40.0 | 800 | 1.8152 | 53.7118 | |
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| 0.0323 | 50.0 | 1000 | 1.8110 | 53.4568 | |
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### Framework versions |
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- Transformers 4.40.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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