---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- balbus-classifier
metrics:
- accuracy
model-index:
- name: whisper-tiny-ft-balbus
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: Balbus dataset
      type: balbus-classifier
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.955
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# whisper-tiny-ft-balbus

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Balbus dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3438
- Accuracy: 0.955

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 6
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0028        | 1.0   | 900  | 0.5075          | 0.895    |
| 0.717         | 2.0   | 1800 | 0.5615          | 0.915    |
| 0.0009        | 3.0   | 2700 | 0.5231          | 0.905    |
| 0.0002        | 4.0   | 3600 | 0.2390          | 0.95     |
| 0.0           | 5.0   | 4500 | 0.4682          | 0.945    |
| 0.0           | 6.0   | 5400 | 0.3438          | 0.955    |


### Framework versions

- Transformers 4.49.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0