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--- |
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license: apache-2.0 |
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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-libirClean-vs-commonNative-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: librispeech_asr |
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type: librispeech_asr |
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config: clean |
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split: train |
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args: clean |
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metrics: |
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- name: Wer |
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type: wer |
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value: 85.53786155346116 |
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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-libirClean-vs-commonNative-en |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the librispeech_asr dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.3358 |
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- Wer: 85.5379 |
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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: 8 |
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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: 10 |
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- training_steps: 50 |
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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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| 1.2481 | 0.08 | 10 | 3.5688 | 21.1895 | |
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| 0.7793 | 0.16 | 20 | 2.8307 | 38.9990 | |
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| 0.5443 | 0.24 | 30 | 2.4196 | 67.0458 | |
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| 0.4484 | 0.32 | 40 | 2.2903 | 71.1732 | |
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| 0.4086 | 0.4 | 50 | 2.3358 | 85.5379 | |
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### Framework versions |
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- Transformers 4.25.0.dev0 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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