README.md

metadata

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: 0.465

whisper-medium-ft-balbus

This model is a fine-tuned version of openai/whisper-medium on the Balbus dataset dataset. It achieves the following results on the evaluation set:

• Loss: 0.7451
• Accuracy: 0.465

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: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	450	0.6979	0.535
4.2819	2.0	900	1.1246	0.465
0.8774	3.0	1350	0.7451	0.465

Framework versions

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