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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: 0.91
---
<!-- 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: 0.5171
- 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4157 | 1.0 | 113 | 1.1896 | 0.67 |
| 0.7796 | 2.0 | 226 | 0.7259 | 0.75 |
| 0.3832 | 3.0 | 339 | 0.5214 | 0.83 |
| 0.3417 | 4.0 | 452 | 0.4182 | 0.86 |
| 0.2349 | 5.0 | 565 | 0.9444 | 0.73 |
| 0.0056 | 6.0 | 678 | 0.4377 | 0.91 |
| 0.1083 | 7.0 | 791 | 0.5190 | 0.9 |
| 0.0022 | 8.0 | 904 | 0.5642 | 0.89 |
| 0.1358 | 9.0 | 1017 | 0.5125 | 0.91 |
| 0.0016 | 10.0 | 1130 | 0.5171 | 0.91 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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