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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-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 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: 12.234193365466401 |
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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 Basque |
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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 eu dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4369 |
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- Wer: 12.2342 |
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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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| 0.0196 | 4.01 | 1000 | 0.2825 | 15.4725 | |
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| 0.0039 | 9.01 | 2000 | 0.3072 | 14.2270 | |
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| 0.0031 | 14.01 | 3000 | 0.3170 | 13.7652 | |
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| 0.0023 | 19.0 | 4000 | 0.3310 | 13.6640 | |
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| 0.0014 | 24.0 | 5000 | 0.3384 | 13.5749 | |
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| 0.0034 | 29.0 | 6000 | 0.3425 | 13.7450 | |
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| 0.0011 | 33.01 | 7000 | 0.3476 | 13.0990 | |
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| 0.001 | 38.01 | 8000 | 0.3432 | 13.0990 | |
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| 0.0004 | 43.01 | 9000 | 0.3524 | 12.8033 | |
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| 0.0017 | 48.01 | 10000 | 0.3620 | 13.3946 | |
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| 0.0003 | 53.0 | 11000 | 0.3564 | 12.6190 | |
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| 0.0001 | 58.0 | 12000 | 0.3675 | 12.6352 | |
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| 0.0 | 63.0 | 13000 | 0.3878 | 12.4286 | |
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| 0.0 | 67.01 | 14000 | 0.3996 | 12.3577 | |
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| 0.0 | 72.01 | 15000 | 0.4088 | 12.3456 | |
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| 0.0 | 77.01 | 16000 | 0.4167 | 12.3091 | |
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| 0.0 | 82.01 | 17000 | 0.4241 | 12.3112 | |
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| 0.0 | 87.0 | 18000 | 0.4302 | 12.3193 | |
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| 0.0 | 92.0 | 19000 | 0.4351 | 12.2565 | |
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| 0.0 | 97.0 | 20000 | 0.4369 | 12.2342 | |
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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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