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--- |
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base_model: NbAiLab/nb-whisper-small-verbatim |
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license: apache-2.0 |
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metrics: |
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- wer |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: nb-whisper-small-karelian-CodeSwitching |
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results: [] |
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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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# nb-whisper-small-karelian-CodeSwitching |
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This model is a fine-tuned version of [NbAiLab/nb-whisper-small-verbatim](https://huggingface.co/NbAiLab/nb-whisper-small-verbatim) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7241 |
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- Wer: 0.3278 |
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- Cer: 0.0999 |
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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: 5e-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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- distributed_type: multi-GPU |
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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: 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 | Cer | |
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|:-------------:|:-------:|:-----:|:---------------:|:------:|:------:| |
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| 0.1848 | 1.1338 | 500 | 0.6758 | 0.4066 | 0.1227 | |
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| 0.0796 | 2.2676 | 1000 | 0.6685 | 0.3549 | 0.1015 | |
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| 0.0492 | 3.4014 | 1500 | 0.7090 | 0.3758 | 0.1088 | |
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| 0.0426 | 4.5351 | 2000 | 0.7095 | 0.3704 | 0.1083 | |
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| 0.0311 | 5.6689 | 2500 | 0.7148 | 0.3742 | 0.1138 | |
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| 0.027 | 6.8027 | 3000 | 0.7173 | 0.3454 | 0.1004 | |
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| 0.0201 | 7.9365 | 3500 | 0.7261 | 0.3813 | 0.1325 | |
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| 0.0165 | 9.0703 | 4000 | 0.7158 | 0.3417 | 0.0982 | |
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| 0.0179 | 10.2041 | 4500 | 0.7261 | 0.3495 | 0.1036 | |
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| 0.0101 | 11.3379 | 5000 | 0.7275 | 0.3315 | 0.0978 | |
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| 0.0086 | 12.4717 | 5500 | 0.7437 | 0.3400 | 0.1081 | |
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| 0.0058 | 13.6054 | 6000 | 0.7524 | 0.3410 | 0.1026 | |
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| 0.0056 | 14.7392 | 6500 | 0.7256 | 0.3407 | 0.1015 | |
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| 0.0075 | 15.8730 | 7000 | 0.7202 | 0.3312 | 0.0987 | |
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| 0.0047 | 17.0068 | 7500 | 0.7266 | 0.3359 | 0.1025 | |
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| 0.0046 | 18.1406 | 8000 | 0.7271 | 0.3312 | 0.0973 | |
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| 0.0039 | 19.2744 | 8500 | 0.7334 | 0.3353 | 0.0999 | |
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| 0.0025 | 20.4082 | 9000 | 0.7280 | 0.3295 | 0.0987 | |
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| 0.0022 | 21.5420 | 9500 | 0.7290 | 0.3254 | 0.0972 | |
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| 0.0031 | 22.6757 | 10000 | 0.7241 | 0.3278 | 0.0999 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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