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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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metrics: |
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- accuracy |
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- f1 |
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- recall |
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- precision |
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model-index: |
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- name: wav2vec2-base-music_genre_classifier-g4-firstseconds |
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results: [] |
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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_genre_classifier-g4-firstseconds |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4970 |
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- Accuracy: 0.8304 |
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- F1: 0.8244 |
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- Recall: 0.8262 |
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- Precision: 0.8260 |
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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: 3e-05 |
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- train_batch_size: 12 |
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- eval_batch_size: 12 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 15 |
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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 | F1 | Recall | Precision | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:------:|:---------:| |
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| 1.1447 | 1.0 | 2393 | 1.2684 | 0.6524 | 0.6382 | 0.6533 | 0.6527 | |
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| 0.7302 | 2.0 | 4786 | 0.8886 | 0.7458 | 0.7421 | 0.7479 | 0.7637 | |
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| 0.521 | 3.0 | 7179 | 0.8755 | 0.7701 | 0.7686 | 0.7715 | 0.7934 | |
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| 0.3648 | 4.0 | 9572 | 1.0389 | 0.7731 | 0.7723 | 0.7673 | 0.7928 | |
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| 0.6132 | 5.0 | 11965 | 1.0694 | 0.7997 | 0.7955 | 0.7943 | 0.8170 | |
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| 0.6512 | 6.0 | 14358 | 1.2190 | 0.7886 | 0.7864 | 0.7864 | 0.7984 | |
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| 0.0851 | 7.0 | 16751 | 1.2496 | 0.8022 | 0.7959 | 0.7973 | 0.8082 | |
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| 0.0881 | 8.0 | 19144 | 1.2582 | 0.8127 | 0.8088 | 0.8105 | 0.8098 | |
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| 0.1063 | 9.0 | 21537 | 1.4087 | 0.8148 | 0.8119 | 0.8121 | 0.8176 | |
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| 0.4205 | 10.0 | 23930 | 1.4825 | 0.8055 | 0.8001 | 0.8019 | 0.8158 | |
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| 0.0478 | 11.0 | 26323 | 1.4240 | 0.8109 | 0.8023 | 0.8031 | 0.8082 | |
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| 0.0037 | 12.0 | 28716 | 1.3865 | 0.8248 | 0.8182 | 0.8199 | 0.8202 | |
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| 0.0236 | 13.0 | 31109 | 1.4570 | 0.8279 | 0.8230 | 0.8232 | 0.8250 | |
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| 0.0094 | 14.0 | 33502 | 1.4892 | 0.8289 | 0.8227 | 0.8248 | 0.8249 | |
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| 0.0002 | 15.0 | 35895 | 1.4970 | 0.8304 | 0.8244 | 0.8262 | 0.8260 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.0+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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