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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: all
split: train
args: all
metrics:
- name: Accuracy
type: accuracy
value: 0.91
---
<!-- 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: 0.6142
- Accuracy: 0.91
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7559 | 1.0 | 113 | 1.6022 | 0.57 |
| 0.9793 | 2.0 | 226 | 0.9895 | 0.7 |
| 0.8508 | 3.0 | 339 | 0.6379 | 0.78 |
| 0.5114 | 4.0 | 452 | 0.8367 | 0.72 |
| 0.115 | 5.0 | 565 | 0.4465 | 0.88 |
| 0.0239 | 6.0 | 678 | 0.5796 | 0.85 |
| 0.2095 | 7.0 | 791 | 0.6141 | 0.87 |
| 0.0019 | 8.0 | 904 | 0.5765 | 0.88 |
| 0.0012 | 9.0 | 1017 | 0.5393 | 0.87 |
| 0.0013 | 10.0 | 1130 | 0.5126 | 0.92 |
| 0.0008 | 11.0 | 1243 | 0.4751 | 0.91 |
| 0.0006 | 12.0 | 1356 | 0.5002 | 0.91 |
| 0.0005 | 13.0 | 1469 | 0.4905 | 0.91 |
| 0.0006 | 14.0 | 1582 | 0.5577 | 0.91 |
| 0.0004 | 15.0 | 1695 | 0.6326 | 0.9 |
| 0.0004 | 16.0 | 1808 | 0.6188 | 0.92 |
| 0.0004 | 17.0 | 1921 | 0.6420 | 0.91 |
| 0.0003 | 18.0 | 2034 | 0.5999 | 0.91 |
| 0.0003 | 19.0 | 2147 | 0.6105 | 0.91 |
| 0.0003 | 20.0 | 2260 | 0.6142 | 0.91 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu118
- Datasets 2.19.2
- Tokenizers 0.19.1
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