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--- |
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license: apache-2.0 |
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base_model: openai/whisper-medium |
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tags: |
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- whisper-event |
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- generated_from_trainer |
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datasets: |
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- common_voice_14_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper da-nst |
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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: common_voice_14_0 |
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type: common_voice_14_0 |
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config: da |
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split: test |
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args: da |
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metrics: |
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- name: Wer |
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type: wer |
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value: 35.3093792833366 |
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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 da-nst |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the common_voice_14_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7234 |
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- Wer: 35.3094 |
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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: 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: 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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- 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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| 0.0133 | 4.04 | 1000 | 0.6362 | 48.9279 | |
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| 0.0025 | 9.04 | 2000 | 0.6635 | 37.4731 | |
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| 0.0001 | 14.03 | 3000 | 0.6959 | 34.1296 | |
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| 0.0001 | 19.03 | 4000 | 0.7166 | 35.1821 | |
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| 0.0 | 24.03 | 5000 | 0.7234 | 35.3094 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.1 |
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