---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- balbus-classifier
metrics:
- accuracy
model-index:
- name: whisper-medium-ft-balbus
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: Balbus dataset
      type: balbus-classifier
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.98
---

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

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Balbus dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1332
- Accuracy: 0.98

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0033        | 1.0   | 450  | 0.1952          | 0.965    |
| 0.4973        | 2.0   | 900  | 0.0796          | 0.98     |
| 0.0021        | 3.0   | 1350 | 0.1894          | 0.97     |
| 0.3833        | 4.0   | 1800 | 0.0987          | 0.985    |
| 0.0003        | 5.0   | 2250 | 0.0741          | 0.99     |
| 0.0001        | 6.0   | 2700 | 0.1332          | 0.98     |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.19.1