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---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: whisper-small-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: 0.92
---
<!-- 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-small-finetuned-gtzan
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3487
- Accuracy: 0.92
## 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: 4e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4671 | 1.0 | 112 | 0.9088 | 0.74 |
| 0.6277 | 2.0 | 225 | 0.6298 | 0.8 |
| 0.446 | 3.0 | 337 | 0.4495 | 0.86 |
| 0.19 | 4.0 | 450 | 0.3389 | 0.91 |
| 0.2302 | 5.0 | 562 | 0.2954 | 0.93 |
| 0.0031 | 6.0 | 675 | 0.3213 | 0.94 |
| 0.0021 | 6.97 | 784 | 0.3487 | 0.92 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
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