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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: 0.84
---
<!-- 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: 1.0690
- 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: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0298 | 1.0 | 113 | 1.9942 | 0.42 |
| 1.6308 | 2.0 | 226 | 1.7948 | 0.45 |
| 1.4047 | 3.0 | 339 | 1.6728 | 0.4 |
| 1.0438 | 4.0 | 452 | 1.2557 | 0.63 |
| 1.0471 | 5.0 | 565 | 1.0976 | 0.66 |
| 0.8658 | 6.0 | 678 | 0.9722 | 0.64 |
| 0.7625 | 7.0 | 791 | 0.7211 | 0.79 |
| 0.6197 | 8.0 | 904 | 0.9618 | 0.71 |
| 0.2382 | 9.0 | 1017 | 0.5927 | 0.85 |
| 0.275 | 10.0 | 1130 | 0.9532 | 0.75 |
| 0.2681 | 11.0 | 1243 | 1.1366 | 0.76 |
| 0.2315 | 12.0 | 1356 | 1.1621 | 0.79 |
| 0.0142 | 13.0 | 1469 | 0.9571 | 0.84 |
| 0.0151 | 14.0 | 1582 | 0.9650 | 0.84 |
| 0.1348 | 15.0 | 1695 | 1.2902 | 0.8 |
| 0.0082 | 16.0 | 1808 | 1.0652 | 0.83 |
| 0.0054 | 17.0 | 1921 | 0.9985 | 0.83 |
| 0.0049 | 18.0 | 2034 | 1.0041 | 0.85 |
| 0.0052 | 19.0 | 2147 | 1.0800 | 0.85 |
| 0.0044 | 20.0 | 2260 | 1.0690 | 0.84 |
### Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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