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--- |
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language: |
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- ru |
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license: apache-2.0 |
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base_model: openai/whisper-small |
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tags: |
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- generated_from_trainer |
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datasets: |
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- bond005/sberdevices_golos_10h_crowd |
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metrics: |
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- wer |
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model-index: |
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- name: my_model - Val123val |
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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: Sberdevices_golos_10h_crowd |
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type: bond005/sberdevices_golos_10h_crowd |
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args: 'split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 42.241139818232334 |
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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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# my_model - Val123val |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Sberdevices_golos_10h_crowd dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1761 |
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- Wer: 42.2411 |
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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: 8 |
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- seed: 42 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:| |
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| 0.1521 | 0.91 | 500 | 0.1824 | 29.3408 | |
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| 0.0824 | 1.82 | 1000 | 0.1702 | 27.5291 | |
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| 0.0304 | 2.73 | 1500 | 0.1726 | 45.1046 | |
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| 0.0114 | 3.64 | 2000 | 0.1704 | 40.1238 | |
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| 0.0039 | 4.55 | 2500 | 0.1692 | 32.1903 | |
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| 0.0013 | 5.45 | 3000 | 0.1704 | 34.0298 | |
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| 0.0029 | 6.36 | 3500 | 0.1712 | 39.8976 | |
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| 0.0007 | 7.27 | 4000 | 0.1738 | 39.4273 | |
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| 0.0006 | 8.18 | 4500 | 0.1755 | 41.0664 | |
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| 0.0005 | 9.09 | 5000 | 0.1761 | 42.2411 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.2+cpu |
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- Datasets 2.16.0 |
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- Tokenizers 0.15.0 |
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