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---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: wav2vec2-base-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: 0.7307692307692307
---
<!-- 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. -->
# wav2vec2-base-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: 1.2479
- Accuracy: 0.7308
## 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: 10
- eval_batch_size: 10
- 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: 18
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9797 | 1.0 | 70 | 1.9644 | 0.3718 |
| 1.4254 | 2.0 | 140 | 1.7058 | 0.4359 |
| 1.3827 | 3.0 | 210 | 1.3349 | 0.5769 |
| 1.1156 | 4.0 | 280 | 1.2080 | 0.6795 |
| 0.7843 | 5.0 | 350 | 1.1072 | 0.6667 |
| 0.7063 | 6.0 | 420 | 1.2091 | 0.6667 |
| 0.4972 | 7.0 | 490 | 1.0370 | 0.7179 |
| 0.6555 | 8.0 | 560 | 1.1193 | 0.6795 |
| 0.4934 | 9.0 | 630 | 0.9080 | 0.7692 |
| 0.1664 | 10.0 | 700 | 1.2513 | 0.6795 |
| 0.3892 | 11.0 | 770 | 1.3065 | 0.6667 |
| 0.0895 | 12.0 | 840 | 1.2479 | 0.7308 |
### Framework versions
- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0
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