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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: 0.88
---
<!-- 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. -->
# 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: 0.5153
- 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: 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0258 | 1.0 | 113 | 1.7851 | 0.47 |
| 1.5568 | 2.0 | 226 | 1.4525 | 0.48 |
| 0.9996 | 3.0 | 339 | 1.3081 | 0.56 |
| 0.9843 | 4.0 | 452 | 0.8743 | 0.81 |
| 0.5038 | 5.0 | 565 | 0.7456 | 0.8 |
| 0.5988 | 6.0 | 678 | 0.6650 | 0.82 |
| 0.5372 | 7.0 | 791 | 0.7010 | 0.8 |
| 0.2489 | 8.0 | 904 | 0.5241 | 0.87 |
| 0.2511 | 9.0 | 1017 | 0.4765 | 0.89 |
| 0.0771 | 10.0 | 1130 | 0.5153 | 0.88 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.0
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