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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-small |
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tags: |
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- generated_from_trainer |
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datasets: |
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- librispeech_asr |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper-Small En-10m |
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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_asr |
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config: default |
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split: None |
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args: 'config: en, split: test-clean' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 4.148066613669255 |
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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 En-10m |
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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: 0.1610 |
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- Wer: 4.1481 |
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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-07 |
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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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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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: 300 |
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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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| 0.5827 | 5.1282 | 100 | 0.7468 | 3.4509 | |
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| 0.3801 | 10.2564 | 200 | 0.5781 | 3.4856 | |
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| 0.1166 | 15.3846 | 300 | 0.2330 | 3.8872 | |
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| 0.0469 | 20.5128 | 400 | 0.1750 | 4.1053 | |
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| 0.0249 | 25.6410 | 500 | 0.1637 | 4.1277 | |
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| 0.0173 | 30.7692 | 600 | 0.1609 | 4.1297 | |
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| 0.0119 | 35.8974 | 700 | 0.1604 | 4.1358 | |
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| 0.0087 | 41.0256 | 800 | 0.1607 | 4.1501 | |
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| 0.0074 | 46.1538 | 900 | 0.1609 | 4.1460 | |
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| 0.0071 | 51.2821 | 1000 | 0.1610 | 4.1481 | |
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### Framework versions |
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- Transformers 4.41.0.dev0 |
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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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