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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: wav2vec2-base-finetuned-gtzan
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: GTZAN
type: marsyas/gtzan
config: train
split: train
args: train
metrics:
- name: Accuracy
type: accuracy
value: 0.84
---
<!-- 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: 0.8879
- Accuracy: 0.84
## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 17
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9838 | 1.0 | 113 | 1.8627 | 0.37 |
| 1.6128 | 2.0 | 226 | 1.5998 | 0.48 |
| 1.0259 | 3.0 | 339 | 1.3821 | 0.57 |
| 1.2766 | 4.0 | 452 | 1.1708 | 0.66 |
| 0.6014 | 5.0 | 565 | 0.7257 | 0.77 |
| 0.5815 | 6.0 | 678 | 1.0738 | 0.68 |
| 0.7664 | 7.0 | 791 | 0.7244 | 0.8 |
| 0.2303 | 8.0 | 904 | 0.5838 | 0.84 |
| 0.4829 | 9.0 | 1017 | 0.5741 | 0.87 |
| 0.0859 | 10.0 | 1130 | 0.6199 | 0.83 |
| 0.2983 | 11.0 | 1243 | 0.8117 | 0.84 |
| 0.0642 | 12.0 | 1356 | 0.5938 | 0.88 |
| 0.0688 | 13.0 | 1469 | 0.9978 | 0.84 |
| 0.1542 | 14.0 | 1582 | 0.7437 | 0.85 |
| 0.0117 | 15.0 | 1695 | 0.9100 | 0.84 |
| 0.039 | 16.0 | 1808 | 0.7757 | 0.85 |
| 0.0661 | 17.0 | 1921 | 0.8879 | 0.84 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1
- Datasets 2.14.0
- Tokenizers 0.13.3
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