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--- |
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library_name: transformers |
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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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- balbus-classifier |
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metrics: |
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- accuracy |
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model-index: |
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- name: miosipof/whisper-small-ft-balbus-sep28k-v1 |
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results: |
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- task: |
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name: Audio Classification |
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type: audio-classification |
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dataset: |
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name: Apple dataset |
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type: balbus-classifier |
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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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- name: Accuracy |
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type: accuracy |
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value: 0.7953596287703016 |
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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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# miosipof/whisper-small-ft-balbus-sep28k-v1 |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Apple dataset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5668 |
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- Accuracy: 0.7954 |
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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: 0.0001 |
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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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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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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_ratio: 0.2 |
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- num_epochs: 3 |
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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 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 404 | 0.4751 | 0.7748 | |
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| 0.494 | 2.0 | 808 | 0.4533 | 0.7901 | |
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| 0.3256 | 3.0 | 1212 | 0.5668 | 0.7954 | |
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### Framework versions |
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- Transformers 4.48.1 |
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- Pytorch 2.2.0 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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