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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: all
split: train
args: all
metrics:
- name: Accuracy
type: accuracy
value: 0.81
---
<!-- 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: 0.7472
- Accuracy: 0.81
## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 2.2042 | 1.0 | 112 | 0.27 | 2.1274 |
| 1.7875 | 2.0 | 225 | 0.51 | 1.6840 |
| 1.4927 | 3.0 | 337 | 0.57 | 1.3809 |
| 1.2344 | 4.0 | 450 | 0.64 | 1.2021 |
| 1.2579 | 5.0 | 562 | 0.62 | 1.1646 |
| 0.9661 | 6.0 | 675 | 0.65 | 1.0412 |
| 1.0119 | 7.0 | 787 | 0.74 | 0.8671 |
| 0.8629 | 8.0 | 900 | 0.66 | 0.9364 |
| 0.607 | 9.0 | 1012 | 0.75 | 0.8867 |
| 0.5699 | 10.0 | 1125 | 0.78 | 0.7432 |
| 0.5128 | 11.0 | 1237 | 0.76 | 0.8212 |
| 0.4203 | 12.0 | 1350 | 0.77 | 0.8128 |
| 0.348 | 13.0 | 1462 | 0.81 | 0.7472 |
| 0.3869 | 14.0 | 1575 | 0.8 | 0.7456 |
| 0.2129 | 14.93 | 1680 | 0.79 | 0.7243 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.0
- Datasets 2.18.0
- Tokenizers 0.15.2
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