metadata
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- gtzan
metrics:
- accuracy
model-index:
- name: whisper-tiny-finetuned-gtzan
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: gtzan
type: gtzan
config: all
split: train
args: all
metrics:
- name: Accuracy
type: accuracy
value: 0.865
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: 0.5357
- Accuracy: 0.865
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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|---|---|---|---|---|
| 1.8988 | 1.0 | 50 | 0.475 | 1.8064 |
| 1.2155 | 2.0 | 100 | 0.66 | 1.2221 |
| 0.9136 | 3.0 | 150 | 0.76 | 0.9259 |
| 0.7999 | 4.0 | 200 | 0.8 | 0.7412 |
| 0.4499 | 5.0 | 250 | 0.785 | 0.6758 |
| 0.2986 | 6.0 | 300 | 0.845 | 0.5601 |
| 0.2432 | 7.0 | 350 | 0.825 | 0.5678 |
| 0.1316 | 8.0 | 400 | 0.845 | 0.5153 |
| 0.1685 | 9.0 | 450 | 0.86 | 0.4840 |
| 0.1344 | 10.0 | 500 | 0.86 | 0.4803 |
| 0.0499 | 11.0 | 550 | 0.5167 | 0.855 |
| 0.0969 | 12.0 | 600 | 0.5370 | 0.85 |
| 0.0351 | 13.0 | 650 | 0.5022 | 0.86 |
| 0.0452 | 14.0 | 700 | 0.5289 | 0.855 |
| 0.0167 | 15.0 | 750 | 0.5357 | 0.865 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1