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: 0.4064
- 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: 16
- eval_batch_size: 16
- 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 |
|---|---|---|---|---|
| 0.988 | 1.0 | 57 | 1.4201 | 0.58 |
| 0.4825 | 2.0 | 114 | 0.7614 | 0.83 |
| 0.5993 | 3.0 | 171 | 0.5825 | 0.83 |
| 0.1427 | 4.0 | 228 | 0.4283 | 0.88 |
| 0.0461 | 5.0 | 285 | 0.3900 | 0.88 |
| 0.0438 | 6.0 | 342 | 0.4485 | 0.86 |
| 0.0171 | 7.0 | 399 | 0.3320 | 0.91 |
| 0.0182 | 8.0 | 456 | 0.3799 | 0.9 |
| 0.0066 | 9.0 | 513 | 0.3901 | 0.88 |
| 0.0077 | 10.0 | 570 | 0.4064 | 0.89 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3