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: 0.9
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: 0.5279
- Accuracy: 0.9
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: 12
- eval_batch_size: 12
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.3629 | 1.0 | 75 | 1.2791 | 0.6 |
| 0.6712 | 2.0 | 150 | 0.7613 | 0.75 |
| 0.5613 | 3.0 | 225 | 0.6708 | 0.77 |
| 0.2594 | 4.0 | 300 | 0.4979 | 0.86 |
| 0.0944 | 5.0 | 375 | 0.5922 | 0.85 |
| 0.1038 | 6.0 | 450 | 0.4702 | 0.89 |
| 0.0077 | 7.0 | 525 | 0.7109 | 0.85 |
| 0.0036 | 8.0 | 600 | 0.5821 | 0.87 |
| 0.0049 | 9.0 | 675 | 0.5013 | 0.9 |
| 0.0025 | 10.0 | 750 | 0.5279 | 0.9 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 1.13.1
- Datasets 2.13.1
- Tokenizers 0.13.3