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--- |
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language: |
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- gl |
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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_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-V3 Galician |
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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 gl |
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type: mozilla-foundation/common_voice_13_0 |
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config: gl |
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split: validation |
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args: gl |
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metrics: |
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- name: Wer |
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type: wer |
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value: 5.309030539895549 |
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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 Galician |
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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_13_0 gl dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2735 |
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- Wer: 5.3090 |
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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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- 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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| 0.0761 | 5.83 | 1000 | 0.1531 | 6.0959 | |
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| 0.0148 | 11.66 | 2000 | 0.1874 | 5.7327 | |
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| 0.0076 | 17.49 | 3000 | 0.2062 | 5.7587 | |
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| 0.0035 | 23.32 | 4000 | 0.2196 | 5.4491 | |
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| 0.0029 | 29.15 | 5000 | 0.2265 | 5.5892 | |
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| 0.0027 | 34.99 | 6000 | 0.2376 | 5.8365 | |
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| 0.0028 | 40.82 | 7000 | 0.2396 | 5.6964 | |
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| 0.0021 | 46.65 | 8000 | 0.2449 | 5.4820 | |
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| 0.0012 | 52.48 | 9000 | 0.2438 | 5.4491 | |
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| 0.0014 | 58.31 | 10000 | 0.2490 | 5.5581 | |
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| 0.0009 | 64.14 | 11000 | 0.2462 | 5.3696 | |
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| 0.0006 | 69.97 | 12000 | 0.2598 | 5.6307 | |
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| 0.0008 | 75.8 | 13000 | 0.2543 | 5.6013 | |
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| 0.0003 | 81.63 | 14000 | 0.2582 | 5.3609 | |
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| 0.0003 | 87.46 | 15000 | 0.2591 | 5.3402 | |
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| 0.0003 | 93.29 | 16000 | 0.2657 | 5.3609 | |
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| 0.0002 | 99.13 | 17000 | 0.2661 | 5.3869 | |
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| 0.0001 | 104.96 | 18000 | 0.2704 | 5.3177 | |
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| 0.0001 | 110.79 | 19000 | 0.2750 | 5.3159 | |
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| 0.0001 | 116.62 | 20000 | 0.2735 | 5.3090 | |
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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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