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--- |
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language: |
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- eu |
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license: apache-2.0 |
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base_model: openai/whisper-medium |
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tags: |
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- whisper-event |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_13_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Medium Basque |
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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: mozilla-foundation/common_voice_13_0 eu |
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type: mozilla-foundation/common_voice_13_0 |
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config: eu |
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split: test |
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args: eu |
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metrics: |
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- name: Wer |
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type: wer |
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value: 14.119648426424725 |
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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 Medium Basque |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_13_0 eu dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4119 |
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- Wer: 14.1196 |
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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: 64 |
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- eval_batch_size: 32 |
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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: 10000 |
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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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| 0.0206 | 4.02 | 1000 | 0.2998 | 16.9995 | |
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| 0.0036 | 9.01 | 2000 | 0.3235 | 15.5211 | |
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| 0.0018 | 14.01 | 3000 | 0.3454 | 14.9905 | |
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| 0.0013 | 19.01 | 4000 | 0.3538 | 14.9439 | |
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| 0.0013 | 24.01 | 5000 | 0.3587 | 14.8568 | |
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| 0.0002 | 29.0 | 6000 | 0.3799 | 14.4153 | |
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| 0.0001 | 33.02 | 7000 | 0.3937 | 14.2067 | |
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| 0.0001 | 38.02 | 8000 | 0.4050 | 14.1946 | |
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| 0.0001 | 43.01 | 9000 | 0.4119 | 14.1196 | |
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| 0.0001 | 48.01 | 10000 | 0.4150 | 14.1358 | |
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### Framework versions |
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- Transformers 4.33.0.dev0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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