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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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- hf-asr-leaderboard |
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- generated_from_trainer |
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datasets: |
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- google/fleurs |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small en - Stan |
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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: fleurs |
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type: google/fleurs |
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config: en_us |
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split: None |
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args: 'config: en, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 8.637757947573899 |
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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 - Stan |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the fleurs dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3236 |
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- Wer: 8.6378 |
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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: 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: 200 |
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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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| 0.5755 | 0.61 | 100 | 0.5716 | 8.6029 | |
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| 0.1769 | 1.23 | 200 | 0.2722 | 8.3659 | |
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| 0.1153 | 1.84 | 300 | 0.2791 | 8.7842 | |
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| 0.0356 | 2.45 | 400 | 0.2852 | 8.7981 | |
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| 0.0208 | 3.07 | 500 | 0.2923 | 8.6866 | |
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| 0.0105 | 3.68 | 600 | 0.3050 | 8.6517 | |
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| 0.0032 | 4.29 | 700 | 0.3126 | 8.6238 | |
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| 0.0033 | 4.91 | 800 | 0.3174 | 8.6308 | |
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| 0.0028 | 5.52 | 900 | 0.3227 | 8.5611 | |
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| 0.0017 | 6.13 | 1000 | 0.3236 | 8.6378 | |
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### Framework versions |
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- Transformers 4.39.1 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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