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: 0.9
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: 0.4744
- 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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 |
|---|---|---|---|---|
| 0.0107 | 0.98 | 28 | 0.5000 | 0.86 |
| 0.1932 | 2.0 | 57 | 0.6231 | 0.85 |
| 0.0589 | 2.98 | 85 | 0.7759 | 0.81 |
| 0.0475 | 4.0 | 114 | 0.4744 | 0.9 |
| 0.0303 | 4.98 | 142 | 0.6446 | 0.88 |
| 0.0037 | 6.0 | 171 | 0.4784 | 0.88 |
| 0.0014 | 6.98 | 199 | 0.6325 | 0.86 |
| 0.0015 | 8.0 | 228 | 0.6423 | 0.88 |
| 0.0012 | 8.98 | 256 | 0.5485 | 0.89 |
| 0.0231 | 9.82 | 280 | 0.5532 | 0.89 |
Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3