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---
license: apache-2.0
base_model: openai/whisper-base.en
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: whisper-base.en-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-base.en-finetuned-gtzan
This model is a fine-tuned version of [openai/whisper-base.en](https://huggingface.co/openai/whisper-base.en) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3412
- 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5696 | 0.99 | 56 | 1.3573 | 0.62 |
| 0.9913 | 2.0 | 113 | 0.7820 | 0.77 |
| 0.4771 | 2.99 | 169 | 0.4873 | 0.84 |
| 0.4411 | 4.0 | 226 | 0.3367 | 0.91 |
| 0.1615 | 4.99 | 282 | 0.3412 | 0.92 |
| 0.1339 | 6.0 | 339 | 0.4125 | 0.91 |
| 0.0331 | 6.99 | 395 | 0.4773 | 0.89 |
| 0.0382 | 8.0 | 452 | 0.4282 | 0.88 |
| 0.049 | 8.99 | 508 | 0.4634 | 0.9 |
| 0.0312 | 9.91 | 560 | 0.4444 | 0.9 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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