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--- |
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license: apache-2.0 |
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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-small-mn-12 |
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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-small-mn-12 |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2949 |
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- Wer: 32.3301 |
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- Cer: 13.3493 |
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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: 32 |
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- eval_batch_size: 32 |
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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: 25000 |
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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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| 0.3012 | 1.05 | 1000 | 0.3749 | 43.2379 | 17.6739 | |
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| 0.2171 | 2.11 | 2000 | 0.3012 | 36.7435 | 15.2029 | |
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| 0.1732 | 3.16 | 3000 | 0.2823 | 33.4225 | 13.7561 | |
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| 0.145 | 4.21 | 4000 | 0.2822 | 32.4995 | 13.2436 | |
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| 0.1159 | 5.27 | 5000 | 0.2949 | 32.3301 | 13.3493 | |
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| 0.0863 | 6.32 | 6000 | 0.3116 | 32.7234 | 13.3892 | |
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| 0.0685 | 7.38 | 7000 | 0.3343 | 32.4776 | 13.3077 | |
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| 0.0506 | 8.43 | 8000 | 0.3584 | 33.3952 | 13.7736 | |
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| 0.0336 | 9.48 | 9000 | 0.3861 | 33.7011 | 13.8493 | |
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| 0.0215 | 10.54 | 10000 | 0.4193 | 33.7011 | 14.0140 | |
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| 0.0141 | 11.59 | 11000 | 0.4463 | 34.0343 | 14.0298 | |
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| 0.0089 | 12.64 | 12000 | 0.4660 | 33.6137 | 13.8052 | |
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| 0.0057 | 13.7 | 13000 | 0.4913 | 33.9797 | 13.9849 | |
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| 0.0039 | 14.75 | 14000 | 0.5078 | 33.9906 | 14.0656 | |
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| 0.0033 | 15.81 | 15000 | 0.5244 | 33.7721 | 13.9192 | |
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| 0.0024 | 16.86 | 16000 | 0.5358 | 33.7612 | 13.7910 | |
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| 0.0018 | 17.91 | 17000 | 0.5469 | 33.6465 | 13.8468 | |
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| 0.0013 | 18.97 | 18000 | 0.5614 | 33.6683 | 13.7553 | |
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| 0.0014 | 20.02 | 19000 | 0.5707 | 33.6574 | 13.8884 | |
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| 0.0006 | 21.07 | 20000 | 0.5835 | 34.0671 | 14.0764 | |
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| 0.0007 | 22.13 | 21000 | 0.5927 | 33.9742 | 14.0772 | |
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| 0.0005 | 23.18 | 22000 | 0.5994 | 34.0398 | 14.0290 | |
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| 0.0004 | 24.24 | 23000 | 0.6067 | 33.9469 | 13.9217 | |
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| 0.0003 | 25.29 | 24000 | 0.6109 | 33.9688 | 13.9591 | |
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| 0.0003 | 26.34 | 25000 | 0.6130 | 33.8267 | 13.8360 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.1.dev0 |
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- Tokenizers 0.13.2 |
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