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---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/wav2vec2-base-100k-voxpopuli
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: wav2vec2-base-100k-voxpopuli-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: 0.87
---
<!-- 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-100k-voxpopuli-finetuned-gtzan
This model is a fine-tuned version of [facebook/wav2vec2-base-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-base-100k-voxpopuli) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9034
- Accuracy: 0.87
## 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: 4
- eval_batch_size: 4
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1924 | 1.0 | 225 | 2.1487 | 0.27 |
| 1.8417 | 2.0 | 450 | 1.8767 | 0.38 |
| 1.6017 | 3.0 | 675 | 1.5778 | 0.51 |
| 1.3497 | 4.0 | 900 | 1.4785 | 0.4 |
| 1.2631 | 5.0 | 1125 | 1.3103 | 0.58 |
| 0.8172 | 6.0 | 1350 | 1.1736 | 0.63 |
| 1.1657 | 7.0 | 1575 | 0.9690 | 0.74 |
| 1.1711 | 8.0 | 1800 | 1.3609 | 0.63 |
| 0.5033 | 9.0 | 2025 | 0.7300 | 0.83 |
| 0.4104 | 10.0 | 2250 | 0.9866 | 0.72 |
| 0.318 | 11.0 | 2475 | 0.8159 | 0.81 |
| 0.1074 | 12.0 | 2700 | 0.8024 | 0.85 |
| 0.093 | 13.0 | 2925 | 0.8285 | 0.85 |
| 0.7407 | 14.0 | 3150 | 0.8591 | 0.87 |
| 0.027 | 15.0 | 3375 | 0.9574 | 0.84 |
| 0.4564 | 16.0 | 3600 | 0.9762 | 0.85 |
| 0.0198 | 17.0 | 3825 | 0.9204 | 0.85 |
| 0.5467 | 18.0 | 4050 | 0.8703 | 0.87 |
| 0.2644 | 19.0 | 4275 | 0.8855 | 0.87 |
| 0.013 | 20.0 | 4500 | 0.9034 | 0.87 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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