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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-small |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-small-CV_Fleurs_AMMI_ALFFA-sw-100hrs-v1 |
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results: [] |
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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-CV_Fleurs_AMMI_ALFFA-sw-100hrs-v1 |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4908 |
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- Wer: 0.1975 |
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- Cer: 0.0747 |
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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-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 4 |
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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: Use adamw_hf with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 100 |
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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 | Cer | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:| |
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| 1.766 | 1.0 | 3941 | 0.4901 | 0.3532 | 0.1359 | |
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| 0.5754 | 2.0 | 7882 | 0.3695 | 0.2248 | 0.0827 | |
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| 0.3572 | 3.0 | 11823 | 0.3460 | 0.1895 | 0.0662 | |
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| 0.2438 | 4.0 | 15764 | 0.3584 | 0.2005 | 0.0812 | |
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| 0.1872 | 5.0 | 19705 | 0.3732 | 0.2092 | 0.0885 | |
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| 0.1594 | 6.0 | 23646 | 0.3998 | 0.1917 | 0.0704 | |
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| 0.1483 | 7.0 | 27587 | 0.4195 | 0.2008 | 0.0754 | |
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| 0.1437 | 8.0 | 31528 | 0.4354 | 0.2083 | 0.0791 | |
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| 0.1413 | 9.0 | 35469 | 0.4415 | 0.1969 | 0.0729 | |
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| 0.1392 | 10.0 | 39410 | 0.4553 | 0.1995 | 0.0766 | |
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| 0.1312 | 11.0 | 43351 | 0.4681 | 0.2010 | 0.0786 | |
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| 0.1095 | 12.0 | 47292 | 0.4726 | 0.2014 | 0.0819 | |
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| 0.0945 | 13.0 | 51233 | 0.4908 | 0.1975 | 0.0747 | |
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### Framework versions |
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- Transformers 4.46.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.1 |
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