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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-v3 |
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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_16_1 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Large-V3 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_16_1 eu |
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type: mozilla-foundation/common_voice_16_1 |
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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: 6.887994372362044 |
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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-V3 Basque |
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on the mozilla-foundation/common_voice_16_1 eu dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3688 |
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- Wer: 6.8880 |
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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: 8 |
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- total_train_batch_size: 256 |
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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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| 0.0095 | 10.04 | 1000 | 0.2023 | 9.6803 | |
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| 0.0032 | 20.08 | 2000 | 0.2153 | 9.0521 | |
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| 0.0023 | 30.11 | 3000 | 0.2234 | 8.8645 | |
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| 0.0023 | 40.15 | 4000 | 0.2278 | 8.4366 | |
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| 0.0012 | 50.19 | 5000 | 0.2260 | 7.9911 | |
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| 0.0005 | 60.23 | 6000 | 0.2435 | 7.9060 | |
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| 0.0013 | 70.26 | 7000 | 0.2254 | 7.8484 | |
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| 0.0004 | 80.3 | 8000 | 0.2367 | 7.4830 | |
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| 0.0008 | 90.34 | 9000 | 0.2289 | 7.4420 | |
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| 0.0007 | 100.38 | 10000 | 0.2385 | 7.5319 | |
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| 0.001 | 110.41 | 11000 | 0.2293 | 7.6325 | |
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| 0.0001 | 120.45 | 12000 | 0.2473 | 7.1430 | |
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| 0.0001 | 130.49 | 13000 | 0.2488 | 7.1870 | |
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| 0.0004 | 140.53 | 14000 | 0.2398 | 7.1831 | |
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| 0.0 | 150.56 | 15000 | 0.2620 | 7.0590 | |
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| 0.0001 | 160.6 | 16000 | 0.2547 | 7.1967 | |
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| 0.0 | 170.64 | 17000 | 0.2768 | 7.0736 | |
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| 0.0 | 180.68 | 18000 | 0.2878 | 7.0004 | |
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| 0.0 | 190.72 | 19000 | 0.2962 | 6.9466 | |
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| 0.0013 | 200.75 | 20000 | 0.2354 | 7.6042 | |
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| 0.0 | 210.79 | 21000 | 0.2720 | 6.8948 | |
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| 0.0 | 220.83 | 22000 | 0.2865 | 6.8987 | |
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| 0.0 | 230.87 | 23000 | 0.2954 | 6.8890 | |
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| 0.0 | 240.9 | 24000 | 0.3031 | 6.8821 | |
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| 0.0 | 250.94 | 25000 | 0.3102 | 6.8772 | |
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| 0.0 | 260.98 | 26000 | 0.3166 | 6.8899 | |
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| 0.0 | 271.02 | 27000 | 0.3233 | 6.8919 | |
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| 0.0 | 281.05 | 28000 | 0.3248 | 6.8919 | |
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| 0.0 | 291.09 | 29000 | 0.3363 | 6.9026 | |
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| 0.0 | 301.13 | 30000 | 0.3419 | 6.9085 | |
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| 0.0 | 311.17 | 31000 | 0.3471 | 6.8851 | |
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| 0.0 | 321.2 | 32000 | 0.3526 | 6.8704 | |
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| 0.0 | 331.24 | 33000 | 0.3570 | 6.8831 | |
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| 0.0 | 341.28 | 34000 | 0.3614 | 6.8851 | |
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| 0.0 | 351.32 | 35000 | 0.3645 | 6.8782 | |
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| 0.0 | 361.36 | 36000 | 0.3663 | 6.8714 | |
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| 0.0 | 371.39 | 37000 | 0.3677 | 6.8675 | |
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| 0.0 | 381.43 | 38000 | 0.3681 | 6.8802 | |
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| 0.0 | 391.47 | 39000 | 0.3686 | 6.8880 | |
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| 0.0 | 401.51 | 40000 | 0.3688 | 6.8880 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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