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---
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: 0.85
---
<!-- 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: 0.8628
- Accuracy: 0.85
## 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: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.269 | 1.0 | 113 | 1.2992 | 0.58 |
| 0.7151 | 2.0 | 226 | 0.8213 | 0.74 |
| 0.6653 | 3.0 | 339 | 0.5565 | 0.82 |
| 0.2204 | 4.0 | 452 | 0.6119 | 0.83 |
| 0.1591 | 5.0 | 565 | 0.6247 | 0.88 |
| 0.006 | 6.0 | 678 | 0.6778 | 0.86 |
| 0.0066 | 7.0 | 791 | 0.8567 | 0.84 |
| 0.002 | 8.0 | 904 | 0.7583 | 0.87 |
| 0.0016 | 9.0 | 1017 | 0.9243 | 0.85 |
| 0.0015 | 10.0 | 1130 | 0.8628 | 0.85 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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