metadata
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: whisper-base-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: 0.62
whisper-base-finetuned-gtzan
This model is a fine-tuned version of openai/whisper-base on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 3.8944
- Accuracy: 0.62
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: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.3577 | 1.0 | 200 | 1.9551 | 0.35 |
| 2.0492 | 2.0 | 400 | 2.0333 | 0.27 |
| 2.0331 | 3.0 | 600 | 1.9196 | 0.3 |
| 1.3732 | 4.0 | 800 | 1.6705 | 0.34 |
| 1.7021 | 5.0 | 1000 | 1.7006 | 0.335 |
| 1.907 | 6.0 | 1200 | 1.7489 | 0.36 |
| 1.611 | 7.0 | 1400 | 1.5347 | 0.45 |
| 1.1989 | 8.0 | 1600 | 1.4835 | 0.465 |
| 2.0049 | 9.0 | 1800 | 1.3681 | 0.525 |
| 0.9562 | 10.0 | 2000 | 1.4732 | 0.49 |
| 0.4145 | 11.0 | 2200 | 1.2645 | 0.555 |
| 1.5859 | 12.0 | 2400 | 1.3992 | 0.51 |
| 1.5115 | 13.0 | 2600 | 1.2638 | 0.545 |
| 0.9777 | 14.0 | 2800 | 1.4003 | 0.57 |
| 0.831 | 15.0 | 3000 | 1.3377 | 0.575 |
| 1.3201 | 16.0 | 3200 | 1.5033 | 0.575 |
| 1.1711 | 17.0 | 3400 | 1.5239 | 0.555 |
| 0.4201 | 18.0 | 3600 | 1.6902 | 0.555 |
| 0.346 | 19.0 | 3800 | 1.9733 | 0.525 |
| 0.5619 | 20.0 | 4000 | 2.1321 | 0.555 |
| 0.645 | 21.0 | 4200 | 2.1219 | 0.625 |
| 0.2672 | 22.0 | 4400 | 2.2037 | 0.555 |
| 0.2826 | 23.0 | 4600 | 2.7297 | 0.565 |
| 0.4265 | 24.0 | 4800 | 3.3848 | 0.5 |
| 0.0319 | 25.0 | 5000 | 3.5627 | 0.59 |
| 0.0024 | 26.0 | 5200 | 3.7420 | 0.6 |
| 0.0332 | 27.0 | 5400 | 3.7159 | 0.63 |
| 0.0009 | 28.0 | 5600 | 3.8011 | 0.635 |
| 0.0001 | 29.0 | 5800 | 3.8852 | 0.615 |
| 0.0001 | 30.0 | 6000 | 3.8944 | 0.62 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3