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--- |
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library_name: transformers |
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language: |
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- ug |
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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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- THUGY20 |
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metrics: |
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- cer |
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- wer |
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model-index: |
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- name: Whisper Small Fine-tuned with THUYG20 Uyghur Dataset |
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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: 'THUGY20: A free Uyghur speech database' |
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type: THUGY20 |
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metrics: |
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- name: Cer |
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type: cer |
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value: 4.927369689396644 |
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- name: Wer |
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type: wer |
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value: 17.940071709066075 |
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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 Fine-tuned with THUYG20 Uyghur Dataset |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the THUGY20: A free Uyghur speech database dataset. |
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It achieves the following results on the test set of THUGY20: |
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- Loss: 0.7473 |
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- Wer Ortho: 18.0908 |
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- Wer: 17.9401 |
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- Cer: 4.9274 |
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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: 0.0001 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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- optimizer: Use 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: 50 |
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- training_steps: 4000 |
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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 Ortho | Wer | Cer | |
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|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|:-------:| |
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| 0.3815 | 0.8058 | 500 | 0.7944 | 34.8819 | 34.7960 | 10.4265 | |
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| 0.1343 | 1.6116 | 1000 | 0.7441 | 28.3393 | 28.3550 | 8.3051 | |
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| 0.0646 | 2.4174 | 1500 | 0.7396 | 27.7378 | 27.5653 | 8.5366 | |
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| 0.0311 | 3.2232 | 2000 | 0.6984 | 25.1910 | 24.9445 | 7.5643 | |
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| 0.0176 | 4.0290 | 2500 | 0.6934 | 21.3709 | 21.2523 | 5.8316 | |
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| 0.0075 | 4.8348 | 3000 | 0.7654 | 20.5541 | 20.3603 | 5.7519 | |
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| 0.0023 | 5.6406 | 3500 | 0.7686 | 18.7582 | 18.5846 | 5.1923 | |
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| 0.0004 | 6.4464 | 4000 | 0.7473 | 18.0908 | 17.9401 | 4.9274 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
