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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-medium |
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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: whisper-medium-ft-balbus |
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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: Balbus dataset |
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type: balbus-classifier |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.465 |
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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-medium-ft-balbus |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Balbus dataset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7451 |
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- Accuracy: 0.465 |
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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: 5e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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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_ratio: 0.1 |
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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 | 450 | 0.6979 | 0.535 | |
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| 4.2819 | 2.0 | 900 | 1.1246 | 0.465 | |
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| 0.8774 | 3.0 | 1350 | 0.7451 | 0.465 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.19.1 |
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