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---
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library_name: transformers
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license: apache-2.0
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base_model: facebook/wav2vec2-base
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tags:
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- generated_from_trainer
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datasets:
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- marsyas/gtzan
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metrics:
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- accuracy
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model-index:
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- name: wav2vec2-base-finetuned-gtzan
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results:
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- task:
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name: Audio Classification
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type: audio-classification
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dataset:
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name: GTZAN
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type: marsyas/gtzan
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config: all
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split: train
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args: all
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.7307692307692307
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# wav2vec2-base-finetuned-gtzan
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.2479
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- Accuracy: 0.7308
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 10
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- eval_batch_size: 10
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 18
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 1.9797 | 1.0 | 70 | 1.9644 | 0.3718 |
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| 1.4254 | 2.0 | 140 | 1.7058 | 0.4359 |
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| 1.3827 | 3.0 | 210 | 1.3349 | 0.5769 |
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| 1.1156 | 4.0 | 280 | 1.2080 | 0.6795 |
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| 0.7843 | 5.0 | 350 | 1.1072 | 0.6667 |
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| 0.7063 | 6.0 | 420 | 1.2091 | 0.6667 |
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| 0.4972 | 7.0 | 490 | 1.0370 | 0.7179 |
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| 0.6555 | 8.0 | 560 | 1.1193 | 0.6795 |
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| 0.4934 | 9.0 | 630 | 0.9080 | 0.7692 |
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| 0.1664 | 10.0 | 700 | 1.2513 | 0.6795 |
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| 0.3892 | 11.0 | 770 | 1.3065 | 0.6667 |
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| 0.0895 | 12.0 | 840 | 1.2479 | 0.7308 |
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### Framework versions
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- Transformers 4.45.1
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- Pytorch 2.4.1+cu121
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- Datasets 3.0.1
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- Tokenizers 0.20.0
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