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---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: HamzaSidhu786/distilhubert-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: 0.88
---
<!-- 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. -->
# HamzaSidhu786/distilhubert-finetuned-gtzan
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co./facebook/wav2vec2-base) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6028
- Accuracy: 0.88
## 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: 3e-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: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0751 | 1.0 | 113 | 2.0343 | 0.6 |
| 1.5734 | 2.0 | 226 | 1.6338 | 0.58 |
| 1.3801 | 3.0 | 339 | 1.2674 | 0.7 |
| 1.0384 | 4.0 | 452 | 1.1376 | 0.68 |
| 0.973 | 5.0 | 565 | 0.9849 | 0.73 |
| 1.0033 | 6.0 | 678 | 0.7686 | 0.76 |
| 0.6347 | 7.0 | 791 | 0.5909 | 0.87 |
| 0.6537 | 8.0 | 904 | 0.9489 | 0.75 |
| 0.359 | 9.0 | 1017 | 0.7478 | 0.81 |
| 0.2268 | 10.0 | 1130 | 0.6247 | 0.84 |
| 0.2674 | 11.0 | 1243 | 0.6437 | 0.84 |
| 0.2237 | 12.0 | 1356 | 0.7997 | 0.81 |
| 0.1418 | 13.0 | 1469 | 0.7738 | 0.84 |
| 0.1201 | 14.0 | 1582 | 0.5696 | 0.87 |
| 0.019 | 15.0 | 1695 | 0.8173 | 0.84 |
| 0.0175 | 16.0 | 1808 | 0.6395 | 0.88 |
| 0.16 | 17.0 | 1921 | 0.6062 | 0.87 |
| 0.0137 | 18.0 | 2034 | 0.5422 | 0.9 |
| 0.0127 | 19.0 | 2147 | 0.6421 | 0.88 |
| 0.0129 | 20.0 | 2260 | 0.6028 | 0.88 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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