MechaBunny19c commited on
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End of training

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: cc-by-nc-4.0
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+ base_model: facebook/wav2vec2-base-100k-voxpopuli
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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-100k-voxpopuli-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: 0.87
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+ ---
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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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+
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+ # wav2vec2-base-100k-voxpopuli-finetuned-gtzan
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-base-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-base-100k-voxpopuli) on the GTZAN dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.9034
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+ - Accuracy: 0.87
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 4
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+ - eval_batch_size: 4
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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: 20
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 2.1924 | 1.0 | 225 | 2.1487 | 0.27 |
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+ | 1.8417 | 2.0 | 450 | 1.8767 | 0.38 |
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+ | 1.6017 | 3.0 | 675 | 1.5778 | 0.51 |
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+ | 1.3497 | 4.0 | 900 | 1.4785 | 0.4 |
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+ | 1.2631 | 5.0 | 1125 | 1.3103 | 0.58 |
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+ | 0.8172 | 6.0 | 1350 | 1.1736 | 0.63 |
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+ | 1.1657 | 7.0 | 1575 | 0.9690 | 0.74 |
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+ | 1.1711 | 8.0 | 1800 | 1.3609 | 0.63 |
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+ | 0.5033 | 9.0 | 2025 | 0.7300 | 0.83 |
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+ | 0.4104 | 10.0 | 2250 | 0.9866 | 0.72 |
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+ | 0.318 | 11.0 | 2475 | 0.8159 | 0.81 |
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+ | 0.1074 | 12.0 | 2700 | 0.8024 | 0.85 |
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+ | 0.093 | 13.0 | 2925 | 0.8285 | 0.85 |
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+ | 0.7407 | 14.0 | 3150 | 0.8591 | 0.87 |
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+ | 0.027 | 15.0 | 3375 | 0.9574 | 0.84 |
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+ | 0.4564 | 16.0 | 3600 | 0.9762 | 0.85 |
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+ | 0.0198 | 17.0 | 3825 | 0.9204 | 0.85 |
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+ | 0.5467 | 18.0 | 4050 | 0.8703 | 0.87 |
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+ | 0.2644 | 19.0 | 4275 | 0.8855 | 0.87 |
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+ | 0.013 | 20.0 | 4500 | 0.9034 | 0.87 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.4.0+cu121
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+ - Datasets 3.0.0
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+ - Tokenizers 0.19.1
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