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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: 0.87
pipeline_tag: text-to-speech
---
<!-- 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: 0.7650
- Accuracy: 0.87
## 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: 0.0001
- 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_steps: 10
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 2.0205 | 0.3274 | 37 | 1.6041 | 0.41 |
| 1.3349 | 0.6549 | 74 | 0.9462 | 0.67 |
| 1.1646 | 0.9823 | 111 | 0.9334 | 0.72 |
| 0.8737 | 1.3097 | 148 | 0.8974 | 0.64 |
| 0.8703 | 1.6372 | 185 | 0.7014 | 0.78 |
| 0.811 | 1.9646 | 222 | 0.8678 | 0.7 |
| 0.6429 | 2.2920 | 259 | 0.9130 | 0.66 |
| 0.6366 | 2.6195 | 296 | 0.7061 | 0.78 |
| 0.5858 | 2.9469 | 333 | 0.5549 | 0.82 |
| 0.3959 | 3.2743 | 370 | 0.5577 | 0.82 |
| 0.3343 | 3.6018 | 407 | 0.6203 | 0.83 |
| 0.3358 | 3.9292 | 444 | 0.8755 | 0.76 |
| 0.2574 | 4.2566 | 481 | 0.7690 | 0.79 |
| 0.1799 | 4.5841 | 518 | 0.7350 | 0.85 |
| 0.212 | 4.9115 | 555 | 0.6767 | 0.84 |
| 0.1553 | 5.2389 | 592 | 0.7819 | 0.84 |
| 0.1065 | 5.5664 | 629 | 0.9823 | 0.83 |
| 0.1151 | 5.8938 | 666 | 0.7709 | 0.84 |
| 0.0107 | 6.2212 | 703 | 0.7156 | 0.88 |
| 0.0564 | 6.5487 | 740 | 0.7283 | 0.88 |
| 0.0501 | 6.8761 | 777 | 0.7763 | 0.87 |
| 0.0846 | 7.2035 | 814 | 0.8221 | 0.83 |
| 0.0372 | 7.5310 | 851 | 0.7526 | 0.87 |
| 0.0015 | 7.8584 | 888 | 0.7705 | 0.87 |
| 0.0209 | 8.1858 | 925 | 0.7020 | 0.86 |
| 0.0114 | 8.5133 | 962 | 0.8043 | 0.86 |
| 0.0011 | 8.8407 | 999 | 0.7608 | 0.88 |
| 0.0018 | 9.1681 | 1036 | 0.7623 | 0.88 |
| 0.0009 | 9.4956 | 1073 | 0.7708 | 0.87 |
| 0.0219 | 9.8230 | 1110 | 0.7650 | 0.87 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |