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--- |
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language: |
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- lv |
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license: apache-2.0 |
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base_model: arturslogins/whisper-medium-lv |
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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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- ta-dataset/training |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper medium LV - Arturs Logins |
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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: Recorded Voice |
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type: ta-dataset/training |
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config: lv |
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split: test |
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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: 43.705463182897866 |
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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 - Arturs Logins |
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This model is a fine-tuned version of [arturslogins/whisper-medium-lv](https://huggingface.co/arturslogins/whisper-medium-lv) on the Recorded Voice dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0843 |
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- Wer: 43.7055 |
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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: 16 |
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- eval_batch_size: 12 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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: 5000 |
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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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| 0.0097 | 6.3898 | 1000 | 0.9780 | 45.8432 | |
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| 0.0023 | 12.7796 | 2000 | 1.0158 | 44.9525 | |
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| 0.0002 | 19.1693 | 3000 | 1.0549 | 46.1758 | |
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| 0.0001 | 25.5591 | 4000 | 1.0765 | 44.9881 | |
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| 0.0001 | 31.9489 | 5000 | 1.0843 | 43.7055 | |
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### Framework versions |
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- Transformers 4.41.0.dev0 |
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- Pytorch 2.0.1 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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