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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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model-index: |
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- name: openai/whisper-medium |
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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_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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- name: Wer |
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type: wer |
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value: 16.15101446793939 |
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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: google/fleurs ca |
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type: google/fleurs |
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args: 'config: ml, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 20.4 |
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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: projecte-aina/parlament_parla clean |
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type: projecte-aina/parlament_parla |
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args: 'config: ml, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 21.14 |
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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-base |
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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-base](https://huggingface.co/openai/whisper-base) 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: 0.3608 |
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- Wer: 16.1510 |
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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: 40000 |
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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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| 0.4841 | 0.1 | 4000 | 0.5078 | 26.7974 | |
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| 0.3116 | 0.2 | 8000 | 0.4524 | 22.9455 | |
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| 0.3971 | 0.3 | 12000 | 0.4281 | 21.5427 | |
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| 0.2965 | 0.4 | 16000 | 0.4037 | 20.3082 | |
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| 0.2634 | 1.09 | 20000 | 0.3875 | 18.7980 | |
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| 0.2163 | 1.19 | 24000 | 0.3754 | 17.8170 | |
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| 0.3182 | 1.29 | 28000 | 0.3695 | 16.8587 | |
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| 0.2201 | 1.39 | 32000 | 0.3613 | 16.5785 | |
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| 0.155 | 2.08 | 36000 | 0.3633 | 16.3959 | |
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| 0.0904 | 2.18 | 40000 | 0.3608 | 16.1510 | |
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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 2.8.0 |
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- Tokenizers 0.13.2 |
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