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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: openai/whisper-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-base-hu-V2 |
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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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# whisper-base-hu-V2 |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0880 |
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- Wer: 0.0960 |
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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: 7e-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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- num_devices: 2 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 64 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 1000 |
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- num_epochs: 3.0 |
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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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| 0.551 | 0.0904 | 1000 | 0.2710 | 0.2694 | |
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| 0.4016 | 0.1807 | 2000 | 0.2009 | 0.2061 | |
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| 0.3449 | 0.2711 | 3000 | 0.1707 | 0.1770 | |
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| 0.3147 | 0.3614 | 4000 | 0.1588 | 0.1650 | |
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| 0.2936 | 0.4518 | 5000 | 0.1472 | 0.1551 | |
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| 0.2758 | 0.5421 | 6000 | 0.1406 | 0.1479 | |
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| 0.2663 | 0.6325 | 7000 | 0.1322 | 0.1393 | |
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| 0.2613 | 0.7228 | 8000 | 0.1283 | 0.1402 | |
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| 0.2491 | 0.8132 | 9000 | 0.1216 | 0.1319 | |
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| 0.238 | 0.9035 | 10000 | 0.1192 | 0.1291 | |
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| 0.2287 | 0.9939 | 11000 | 0.1151 | 0.1276 | |
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| 0.1798 | 1.0842 | 12000 | 0.1131 | 0.1234 | |
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| 0.1791 | 1.1746 | 13000 | 0.1113 | 0.1186 | |
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| 0.1787 | 1.2649 | 14000 | 0.1085 | 0.1186 | |
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| 0.1771 | 1.3553 | 15000 | 0.1068 | 0.1154 | |
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| 0.1728 | 1.4456 | 16000 | 0.1046 | 0.1135 | |
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| 0.1714 | 1.5360 | 17000 | 0.1029 | 0.1152 | |
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| 0.1706 | 1.6263 | 18000 | 0.1007 | 0.1117 | |
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| 0.163 | 1.7167 | 19000 | 0.0998 | 0.1074 | |
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| 0.1613 | 1.8070 | 20000 | 0.0982 | 0.1075 | |
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| 0.1568 | 1.8974 | 21000 | 0.0967 | 0.1087 | |
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| 0.1525 | 1.9878 | 22000 | 0.0945 | 0.1045 | |
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| 0.1063 | 2.0781 | 23000 | 0.0967 | 0.1046 | |
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| 0.1075 | 2.1684 | 24000 | 0.0951 | 0.1030 | |
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| 0.1035 | 2.2588 | 25000 | 0.0936 | 0.1015 | |
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| 0.1056 | 2.3491 | 26000 | 0.0928 | 0.1013 | |
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| 0.1019 | 2.4395 | 27000 | 0.0921 | 0.1000 | |
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| 0.1004 | 2.5298 | 28000 | 0.0911 | 0.0986 | |
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| 0.0992 | 2.6202 | 29000 | 0.0904 | 0.0980 | |
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| 0.1011 | 2.7105 | 30000 | 0.0898 | 0.0978 | |
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| 0.095 | 2.8009 | 31000 | 0.0892 | 0.0975 | |
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| 0.0975 | 2.8913 | 32000 | 0.0885 | 0.0960 | |
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| 0.0963 | 2.9816 | 33000 | 0.0880 | 0.0962 | |
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### Framework versions |
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- Transformers 4.48.0.dev0 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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