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--- |
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library_name: transformers |
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language: |
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- lv |
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license: apache-2.0 |
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base_model: FelixK7/whisper-medium-lv-ver2 |
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tags: |
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- hf-asr-leaderboard |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_16_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper medium LV - Felikss Kleins |
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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: Common Voice 16.0 |
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type: mozilla-foundation/common_voice_16_0 |
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config: lv |
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split: None |
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args: 'config: lv, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 19.39252336448598 |
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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 medium LV - Felikss Kleins |
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This model is a fine-tuned version of [FelixK7/whisper-medium-lv-ver2](https://huggingface.co/FelixK7/whisper-medium-lv-ver2) on the Common Voice 16.0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2882 |
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- Wer: 19.3925 |
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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: 2e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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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: Use adamw_hf with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 10000 |
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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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| No log | 99.0002 | 200 | 0.1666 | 11.4486 | |
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| 0.0028 | 199.0002 | 400 | 0.2083 | 13.5514 | |
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| 0.0007 | 299.0002 | 600 | 0.2815 | 20.7944 | |
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| 0.0008 | 399.0002 | 800 | 0.2882 | 19.3925 | |
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### Framework versions |
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- Transformers 4.46.0.dev0 |
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- Pytorch 2.0.1 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.1 |
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