metadata
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: whisper-tiny-finetuned-gtzan
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: GTZAN
type: marsyas/gtzan
config: all
split: train
args: all
metrics:
- name: Accuracy
type: accuracy
value: 0.89
whisper-tiny-finetuned-gtzan
This model is a fine-tuned version of openai/whisper-tiny on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 0.7231
- Accuracy: 0.89
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: 6
- eval_batch_size: 6
- 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: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3867 | 1.0 | 150 | 0.4913 | 0.85 |
| 0.6883 | 2.0 | 300 | 0.9527 | 0.81 |
| 0.0056 | 3.0 | 450 | 0.6576 | 0.84 |
| 0.0021 | 4.0 | 600 | 0.7685 | 0.84 |
| 0.0007 | 5.0 | 750 | 0.7602 | 0.87 |
| 0.0005 | 6.0 | 900 | 0.8593 | 0.85 |
| 0.0005 | 7.0 | 1050 | 0.8438 | 0.84 |
| 0.0003 | 8.0 | 1200 | 0.6439 | 0.88 |
| 0.0003 | 9.0 | 1350 | 0.7370 | 0.88 |
| 0.0003 | 10.0 | 1500 | 0.7231 | 0.89 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2