|
--- |
|
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: 0.62 |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# whisper-base-finetuned-gtzan |
|
|
|
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co./openai/whisper-base) on the GTZAN dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 3.8944 |
|
- Accuracy: 0.62 |
|
|
|
## 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: 4 |
|
- eval_batch_size: 4 |
|
- 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: 30 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 2.3577 | 1.0 | 200 | 1.9551 | 0.35 | |
|
| 2.0492 | 2.0 | 400 | 2.0333 | 0.27 | |
|
| 2.0331 | 3.0 | 600 | 1.9196 | 0.3 | |
|
| 1.3732 | 4.0 | 800 | 1.6705 | 0.34 | |
|
| 1.7021 | 5.0 | 1000 | 1.7006 | 0.335 | |
|
| 1.907 | 6.0 | 1200 | 1.7489 | 0.36 | |
|
| 1.611 | 7.0 | 1400 | 1.5347 | 0.45 | |
|
| 1.1989 | 8.0 | 1600 | 1.4835 | 0.465 | |
|
| 2.0049 | 9.0 | 1800 | 1.3681 | 0.525 | |
|
| 0.9562 | 10.0 | 2000 | 1.4732 | 0.49 | |
|
| 0.4145 | 11.0 | 2200 | 1.2645 | 0.555 | |
|
| 1.5859 | 12.0 | 2400 | 1.3992 | 0.51 | |
|
| 1.5115 | 13.0 | 2600 | 1.2638 | 0.545 | |
|
| 0.9777 | 14.0 | 2800 | 1.4003 | 0.57 | |
|
| 0.831 | 15.0 | 3000 | 1.3377 | 0.575 | |
|
| 1.3201 | 16.0 | 3200 | 1.5033 | 0.575 | |
|
| 1.1711 | 17.0 | 3400 | 1.5239 | 0.555 | |
|
| 0.4201 | 18.0 | 3600 | 1.6902 | 0.555 | |
|
| 0.346 | 19.0 | 3800 | 1.9733 | 0.525 | |
|
| 0.5619 | 20.0 | 4000 | 2.1321 | 0.555 | |
|
| 0.645 | 21.0 | 4200 | 2.1219 | 0.625 | |
|
| 0.2672 | 22.0 | 4400 | 2.2037 | 0.555 | |
|
| 0.2826 | 23.0 | 4600 | 2.7297 | 0.565 | |
|
| 0.4265 | 24.0 | 4800 | 3.3848 | 0.5 | |
|
| 0.0319 | 25.0 | 5000 | 3.5627 | 0.59 | |
|
| 0.0024 | 26.0 | 5200 | 3.7420 | 0.6 | |
|
| 0.0332 | 27.0 | 5400 | 3.7159 | 0.63 | |
|
| 0.0009 | 28.0 | 5600 | 3.8011 | 0.635 | |
|
| 0.0001 | 29.0 | 5800 | 3.8852 | 0.615 | |
|
| 0.0001 | 30.0 | 6000 | 3.8944 | 0.62 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.32.1 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.14.4 |
|
- Tokenizers 0.13.3 |
|
|
