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--- |
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language: |
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- ca |
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license: apache-2.0 |
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base_model: openai/whisper-large |
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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 Large Catalan |
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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 ca |
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type: mozilla-foundation/common_voice_13_0 |
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config: ca |
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split: test |
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args: ca |
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metrics: |
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- name: Wer |
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type: wer |
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value: 5.070020005715919 |
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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 Large Catalan |
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This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co./openai/whisper-large) on the mozilla-foundation/common_voice_13_0 ca dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1458 |
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- Wer: 5.0700 |
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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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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:| |
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| 0.1059 | 1.02 | 1000 | 0.1744 | 7.6342 | |
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| 0.0159 | 3.02 | 2000 | 0.1943 | 7.3850 | |
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| 0.0526 | 5.02 | 3000 | 0.1899 | 6.8522 | |
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| 0.058 | 7.02 | 4000 | 0.1782 | 6.7802 | |
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| 0.0161 | 9.02 | 5000 | 0.1995 | 6.6339 | |
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| 0.065 | 11.02 | 6000 | 0.1563 | 6.4544 | |
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| 0.082 | 13.02 | 7000 | 0.1789 | 6.0309 | |
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| 0.0339 | 15.02 | 8000 | 0.1509 | 5.7554 | |
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| 0.0581 | 17.01 | 9000 | 0.1573 | 6.0446 | |
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| 0.0181 | 19.01 | 10000 | 0.1838 | 5.5913 | |
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| 0.0188 | 21.01 | 11000 | 0.1610 | 5.4804 | |
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| 0.0134 | 23.01 | 12000 | 0.1821 | 5.3953 | |
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| 0.008 | 25.01 | 13000 | 0.1748 | 5.3804 | |
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| 0.0071 | 27.01 | 14000 | 0.1858 | 5.4701 | |
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| 0.0371 | 29.01 | 15000 | 0.1610 | 5.6599 | |
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| 0.0076 | 31.01 | 16000 | 0.1571 | 5.1655 | |
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| 0.0181 | 33.01 | 17000 | 0.1449 | 5.4558 | |
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| 0.0522 | 35.0 | 18000 | 0.1340 | 5.8388 | |
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| 0.0356 | 37.0 | 19000 | 0.1458 | 5.0700 | |
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| 0.0132 | 39.0 | 20000 | 0.1310 | 5.1941 | |
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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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