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---
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: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.88
---
<!-- 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-tiny-finetuned-gtzan
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8859
- Accuracy: 0.88
## 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: 8
- eval_batch_size: 8
- 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: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7103 | 1.0 | 113 | 1.4757 | 0.57 |
| 0.8805 | 2.0 | 226 | 0.8030 | 0.74 |
| 0.7231 | 3.0 | 339 | 0.4844 | 0.88 |
| 0.9119 | 4.0 | 452 | 0.6392 | 0.79 |
| 0.2952 | 5.0 | 565 | 0.5729 | 0.83 |
| 0.1099 | 6.0 | 678 | 0.5263 | 0.83 |
| 0.1363 | 7.0 | 791 | 0.4978 | 0.91 |
| 0.0021 | 8.0 | 904 | 0.6480 | 0.89 |
| 0.0413 | 9.0 | 1017 | 0.7381 | 0.87 |
| 0.0023 | 10.0 | 1130 | 0.6896 | 0.9 |
| 0.0006 | 11.0 | 1243 | 0.7574 | 0.89 |
| 0.1621 | 12.0 | 1356 | 0.8407 | 0.88 |
| 0.0005 | 13.0 | 1469 | 0.7967 | 0.89 |
| 0.0005 | 14.0 | 1582 | 0.7795 | 0.89 |
| 0.0004 | 15.0 | 1695 | 0.7795 | 0.9 |
| 0.0003 | 16.0 | 1808 | 0.9152 | 0.87 |
| 0.0003 | 17.0 | 1921 | 0.8594 | 0.88 |
| 0.0003 | 18.0 | 2034 | 0.8481 | 0.88 |
| 0.0003 | 19.0 | 2147 | 0.8471 | 0.88 |
| 0.0545 | 20.0 | 2260 | 0.8859 | 0.88 |
### Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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