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--- |
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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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- facebook/voxpopuli |
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metrics: |
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- wer |
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model-index: |
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- name: WhisperForSpokenNER-end2end |
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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: facebook/voxpopuli de+es+fr+nl |
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type: facebook/voxpopuli |
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config: de+es+fr+nl |
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split: None |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.14642407057340895 |
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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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# WhisperForSpokenNER-end2end |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the facebook/voxpopuli de+es+fr+nl dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3933 |
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- Wer: 0.1464 |
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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: 0.0001 |
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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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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 5000 |
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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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| 0.3562 | 0.36 | 200 | 0.3265 | 0.1920 | |
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| 0.3149 | 0.71 | 400 | 0.3136 | 0.1842 | |
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| 0.2778 | 1.07 | 600 | 0.3204 | 0.1786 | |
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| 0.2288 | 1.43 | 800 | 0.3156 | 0.1717 | |
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| 0.2307 | 1.79 | 1000 | 0.3056 | 0.1708 | |
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| 0.1482 | 2.14 | 1200 | 0.3138 | 0.1682 | |
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| 0.1368 | 2.5 | 1400 | 0.3136 | 0.1656 | |
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| 0.1405 | 2.86 | 1600 | 0.3082 | 0.1617 | |
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| 0.0639 | 3.22 | 1800 | 0.3201 | 0.1612 | |
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| 0.0673 | 3.57 | 2000 | 0.3242 | 0.1612 | |
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| 0.0688 | 3.93 | 2200 | 0.3235 | 0.1584 | |
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| 0.0227 | 4.29 | 2400 | 0.3420 | 0.1558 | |
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| 0.0232 | 4.65 | 2600 | 0.3430 | 0.1525 | |
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| 0.0229 | 5.0 | 2800 | 0.3450 | 0.1528 | |
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| 0.0064 | 5.36 | 3000 | 0.3631 | 0.1498 | |
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| 0.0059 | 5.72 | 3200 | 0.3652 | 0.1482 | |
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| 0.0043 | 6.08 | 3400 | 0.3756 | 0.1482 | |
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| 0.0021 | 6.43 | 3600 | 0.3798 | 0.1477 | |
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| 0.002 | 6.79 | 3800 | 0.3824 | 0.1484 | |
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| 0.0014 | 7.15 | 4000 | 0.3876 | 0.1471 | |
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| 0.0013 | 7.51 | 4200 | 0.3900 | 0.1473 | |
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| 0.0013 | 7.86 | 4400 | 0.3917 | 0.1461 | |
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| 0.0012 | 8.22 | 4600 | 0.3929 | 0.1462 | |
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| 0.0012 | 8.58 | 4800 | 0.3932 | 0.1465 | |
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| 0.0012 | 8.94 | 5000 | 0.3933 | 0.1464 | |
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### Framework versions |
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- Transformers 4.37.0.dev0 |
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- Pytorch 2.1.0 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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