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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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- hf-asr-leaderboard |
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- whisper-event |
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metrics: |
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- wer |
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base_model: openai/whisper-medium |
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model-index: |
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- name: openai/whisper-medium |
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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: mozilla-foundation/common_voice_11_0 ca |
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type: mozilla-foundation/common_voice_11_0 |
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args: 'config: ml, split: test' |
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metrics: |
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- type: wer |
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value: 8.282966640983934 |
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name: Wer |
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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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# openai/whisper-medium |
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This is an automatic speech recognition model that also does punctuation and casing. This model is for research only, **we do not recommend using this model on production environments**. See our [learnings](https://huggingface.co/softcatala/whisper-small-ca/blob/main/TRAINING.md) when training these models. |
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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_11_0 ca dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2029 |
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- Wer: 8.3235 |
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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: 2 |
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- eval_batch_size: 1 |
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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: 20000 |
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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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| 0.2652 | 0.1 | 2000 | 0.3469 | 15.3537 | |
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| 0.3273 | 0.2 | 4000 | 0.3151 | 14.1141 | |
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| 0.2696 | 0.3 | 6000 | 0.2955 | 13.2472 | |
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| 0.1725 | 0.4 | 8000 | 0.2787 | 11.6834 | |
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| 0.1741 | 0.5 | 10000 | 0.2648 | 11.0088 | |
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| 0.2037 | 0.6 | 12000 | 0.2470 | 10.1909 | |
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| 0.1586 | 0.7 | 14000 | 0.2333 | 9.4096 | |
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| 0.1548 | 0.8 | 16000 | 0.2184 | 8.9724 | |
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| 0.1799 | 1.08 | 18000 | 0.2064 | 8.2830 | |
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| 0.1165 | 1.18 | 20000 | 0.2029 | 8.3235 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.10.0+cu102 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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