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README.md
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---
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license: apache-2.0
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base_model: FerhatDk/wav2vec2-base_music_speech_both_classification
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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_music_speech_both_classification-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: 0.85
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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_music_speech_both_classification-finetuned-gtzan
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This model is a fine-tuned version of [FerhatDk/wav2vec2-base_music_speech_both_classification](https://huggingface.co/FerhatDk/wav2vec2-base_music_speech_both_classification) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6167
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- Accuracy: 0.85
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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: 2
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 16
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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: 10
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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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| 2.0009 | 1.0 | 56 | 1.8533 | 0.31 |
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| 1.4898 | 1.99 | 112 | 1.3633 | 0.45 |
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| 1.1394 | 2.99 | 168 | 1.1963 | 0.61 |
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| 0.9214 | 4.0 | 225 | 0.8506 | 0.73 |
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| 0.6922 | 5.0 | 281 | 0.8479 | 0.78 |
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| 0.687 | 5.99 | 337 | 0.7577 | 0.81 |
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| 0.5052 | 6.99 | 393 | 0.7833 | 0.78 |
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| 0.3733 | 8.0 | 450 | 0.6448 | 0.83 |
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| 0.2137 | 9.0 | 506 | 0.5698 | 0.83 |
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| 0.2863 | 9.96 | 560 | 0.6167 | 0.85 |
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### Framework versions
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- Transformers 4.34.0.dev0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.5
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- Tokenizers 0.13.3
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