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--- |
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base_model: openai/whisper-small |
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datasets: |
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- arrow |
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license: apache-2.0 |
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metrics: |
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- wer |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: dialect |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: arrow |
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type: arrow |
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config: default |
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split: train |
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args: default |
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metrics: |
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- type: wer |
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value: 0.0 |
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name: Wer |
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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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# dialect |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the arrow dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0001 |
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- Wer: 0.0 |
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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: 1 |
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- eval_batch_size: 1 |
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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: 100 |
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- num_epochs: 5 |
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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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| 0.0444 | 0.2404 | 1000 | 0.0239 | 3.75 | |
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| 0.0115 | 0.4808 | 2000 | 0.0157 | 1.5385 | |
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| 0.0047 | 0.7212 | 3000 | 0.0844 | 4.4231 | |
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| 0.0153 | 0.9615 | 4000 | 0.0050 | 0.6731 | |
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| 0.0192 | 1.2019 | 5000 | 0.0017 | 0.1923 | |
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| 0.0 | 1.4423 | 6000 | 0.0075 | 0.8654 | |
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| 0.0 | 1.6827 | 7000 | 0.0002 | 0.0962 | |
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| 0.0274 | 1.9231 | 8000 | 0.0195 | 2.2115 | |
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| 0.0 | 2.1635 | 9000 | 0.0179 | 1.0577 | |
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| 0.0402 | 2.4038 | 10000 | 0.0020 | 0.0962 | |
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| 0.0161 | 2.6442 | 11000 | 0.0050 | 0.3846 | |
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| 0.0009 | 2.8846 | 12000 | 0.0048 | 0.2885 | |
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| 0.0 | 3.125 | 13000 | 0.0031 | 0.1923 | |
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| 0.0 | 3.3654 | 14000 | 0.0029 | 0.1923 | |
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| 0.0 | 3.6058 | 15000 | 0.0029 | 0.1923 | |
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| 0.0 | 3.8462 | 16000 | 0.0043 | 0.1923 | |
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| 0.0 | 4.0865 | 17000 | 0.0008 | 0.0962 | |
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| 0.0 | 4.3269 | 18000 | 0.0000 | 0.0 | |
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| 0.0 | 4.5673 | 19000 | 0.0000 | 0.0 | |
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| 0.0 | 4.8077 | 20000 | 0.0001 | 0.0 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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