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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: openai/whisper-large-v3 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- fsicoli/cv19-fleurs |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-large-v3-pt-cv19-fleurs |
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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: fsicoli/cv19-fleurs default |
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type: fsicoli/cv19-fleurs |
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args: default |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.0756 |
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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-large-v3-pt-cv19-fleurs |
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on the fsicoli/cv19-fleurs default dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1823 |
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- Wer: 0.0756 |
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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: 6.25e-06 |
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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: 10000 |
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- training_steps: 50000 |
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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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| 0.0559 | 2.2883 | 5000 | 0.1096 | 0.0730 | |
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| 0.0581 | 4.5767 | 10000 | 0.1326 | 0.0829 | |
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| 0.0225 | 6.8650 | 15000 | 0.1570 | 0.0849 | |
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| 0.0088 | 9.1533 | 20000 | 0.1704 | 0.0840 | |
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| 0.0065 | 11.4416 | 25000 | 0.1823 | 0.0849 | |
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| 0.006 | 13.7300 | 30000 | 0.1808 | 0.0809 | |
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| 0.0055 | 16.0183 | 35000 | 0.1811 | 0.0790 | |
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| 0.0031 | 18.3066 | 40000 | 0.1907 | 0.0784 | |
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| 0.0011 | 20.5950 | 45000 | 0.1852 | 0.0771 | |
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| 0.0003 | 22.8833 | 50000 | 0.1848 | 0.0756 | |
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### Framework versions |
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- Transformers 4.45.0.dev0 |
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- Pytorch 2.4.1 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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