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--- |
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language: |
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- sr |
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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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- espnet/yodas |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small Yodas |
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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: Yodas |
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type: espnet/yodas |
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config: sr |
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split: test |
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args: sr |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.11913993655269652 |
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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 Yodas |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Yodas dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1748 |
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- Wer Ortho: 0.2143 |
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- Wer: 0.1191 |
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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: 16 |
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- eval_batch_size: 8 |
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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: 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 | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:| |
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| 0.7316 | 0.24 | 500 | 0.2554 | 0.2942 | 0.2184 | |
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| 0.6996 | 0.49 | 1000 | 0.2136 | 0.2535 | 0.1563 | |
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| 0.6073 | 0.73 | 1500 | 0.1979 | 0.2374 | 0.1452 | |
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| 0.6032 | 0.98 | 2000 | 0.1872 | 0.2228 | 0.1280 | |
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| 0.4603 | 1.22 | 2500 | 0.1811 | 0.2136 | 0.1218 | |
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| 0.4142 | 1.46 | 3000 | 0.1767 | 0.2152 | 0.1200 | |
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| 0.4457 | 1.71 | 3500 | 0.1759 | 0.2159 | 0.1234 | |
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| 0.4376 | 1.95 | 4000 | 0.1748 | 0.2143 | 0.1191 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.1 |
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