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--- |
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license: apache-2.0 |
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tags: |
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- whisper-event |
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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 Tiny ID - FLEURS-CV |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: google/fleurs |
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type: google/fleurs |
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config: id_id |
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split: test |
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metrics: |
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- type: wer |
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value: 30.8 |
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name: WER |
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- type: cer |
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value: 11.29 |
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name: CER |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: mozilla-foundation/common_voice_11_0 |
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type: mozilla-foundation/common_voice_11_0 |
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config: id |
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split: test |
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metrics: |
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- type: wer |
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value: 32.49 |
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name: WER |
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- type: cer |
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value: 12.25 |
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name: CER |
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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 Tiny ID - FLEURS-CV |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5129 |
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- Wer: 31.1298 |
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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: 32 |
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- eval_batch_size: 16 |
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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: 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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| 0.617 | 1.43 | 500 | 0.5956 | 40.1521 | |
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| 0.4062 | 2.86 | 1000 | 0.4991 | 33.2066 | |
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| 0.2467 | 4.29 | 1500 | 0.4755 | 31.6802 | |
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| 0.1904 | 5.71 | 2000 | 0.4681 | 30.5907 | |
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| 0.118 | 7.14 | 2500 | 0.4776 | 30.9368 | |
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| 0.0941 | 8.57 | 3000 | 0.4831 | 30.7297 | |
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| 0.0771 | 10.0 | 3500 | 0.4912 | 31.1014 | |
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| 0.0536 | 11.43 | 4000 | 0.5043 | 31.2319 | |
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| 0.0502 | 12.86 | 4500 | 0.5113 | 31.2404 | |
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| 0.0418 | 14.29 | 5000 | 0.5129 | 31.1298 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.7.1.dev0 |
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- Tokenizers 0.13.2 |
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