metadata
license: apache-2.0
base_model: openai/whisper-medium.en
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: whisper-medium.en-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: 0.95
whisper-medium.en-finetuned-gtzan
This model is a fine-tuned version of openai/whisper-medium.en on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 0.2885
- Accuracy: 0.95
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: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 16
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.7711 | 1.0 | 112 | 1.6556 | 0.52 |
| 0.5477 | 2.0 | 225 | 0.4738 | 0.85 |
| 0.535 | 3.0 | 337 | 0.3137 | 0.92 |
| 0.231 | 4.0 | 450 | 0.3613 | 0.9 |
| 0.1923 | 5.0 | 562 | 0.2885 | 0.95 |
| 0.0584 | 6.0 | 675 | 0.6531 | 0.86 |
| 0.1783 | 7.0 | 787 | 0.5717 | 0.9 |
| 0.0022 | 8.0 | 900 | 0.4205 | 0.91 |
| 0.1032 | 9.0 | 1012 | 0.4984 | 0.91 |
| 0.0011 | 10.0 | 1125 | 0.3778 | 0.94 |
| 0.0104 | 11.0 | 1237 | 0.3709 | 0.94 |
| 0.0011 | 12.0 | 1350 | 0.4564 | 0.92 |
| 0.0009 | 13.0 | 1462 | 0.3796 | 0.94 |
| 0.0008 | 14.0 | 1575 | 0.3880 | 0.94 |
| 0.0008 | 15.0 | 1687 | 0.3930 | 0.94 |
| 0.0008 | 15.93 | 1792 | 0.3955 | 0.94 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0