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End of training

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README.md ADDED
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+ ---
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+ license: bsd-3-clause
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+ base_model: MIT/ast-finetuned-audioset-10-10-0.4593
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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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+ - f1
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+ model-index:
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+ - name: ast-finetuned-audioset-10-10-0.4593-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: 0.86
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+ - name: F1
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+ type: f1
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+ value: 0.8599999999999999
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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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+ # ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan
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+
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+ This model is a fine-tuned version of [MIT/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593) on the GTZAN dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7149
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+ - Accuracy: 0.86
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+ - F1: 0.8600
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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: 2
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+ - eval_batch_size: 2
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+ - seed: 2024
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 8
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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 | F1 |
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+ |:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
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+ | 0.6891 | 0.9956 | 112 | 0.6422 | 0.76 | 0.76 |
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+ | 0.7267 | 2.0 | 225 | 0.8163 | 0.78 | 0.78 |
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+ | 0.7077 | 2.9956 | 337 | 0.7802 | 0.8 | 0.8000 |
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+ | 0.1884 | 4.0 | 450 | 0.6157 | 0.87 | 0.87 |
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+ | 0.0209 | 4.9956 | 562 | 0.7885 | 0.84 | 0.8400 |
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+ | 0.117 | 6.0 | 675 | 0.6744 | 0.85 | 0.85 |
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+ | 0.0098 | 6.9956 | 787 | 0.6213 | 0.85 | 0.85 |
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+ | 0.0002 | 8.0 | 900 | 1.0599 | 0.82 | 0.82 |
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+ | 0.0001 | 8.9956 | 1012 | 0.7052 | 0.86 | 0.8600 |
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+ | 0.0001 | 10.0 | 1125 | 0.6891 | 0.85 | 0.85 |
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+ | 0.0001 | 10.9956 | 1237 | 0.6718 | 0.86 | 0.8600 |
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+ | 0.0001 | 12.0 | 1350 | 0.6712 | 0.85 | 0.85 |
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+ | 0.0001 | 12.9956 | 1462 | 0.6942 | 0.86 | 0.8600 |
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+ | 0.0001 | 14.0 | 1575 | 0.7002 | 0.86 | 0.8600 |
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+ | 0.0176 | 14.9956 | 1687 | 0.7053 | 0.86 | 0.8600 |
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+ | 0.0001 | 16.0 | 1800 | 0.7140 | 0.86 | 0.8600 |
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+ | 0.0001 | 16.9956 | 1912 | 0.7089 | 0.86 | 0.8600 |
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+ | 0.0 | 18.0 | 2025 | 0.7120 | 0.86 | 0.8600 |
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+ | 0.0628 | 18.9956 | 2137 | 0.7162 | 0.86 | 0.8600 |
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+ | 0.0037 | 19.9111 | 2240 | 0.7149 | 0.86 | 0.8600 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.42.4
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.21.0
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+ - Tokenizers 0.19.1
config.json ADDED
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+ {
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+ "_name_or_path": "MIT/ast-finetuned-audioset-10-10-0.4593",
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+ "architectures": [
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+ "ASTForAudioClassification"
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+ ],
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+ "id2label": {
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+ "0": "blues",
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+ "1": "classical",
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+ "2": "country",
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+ "3": "disco",
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+ "4": "hiphop",
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+ "5": "jazz",
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+ "6": "metal",
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+ "7": "pop",
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+ "8": "reggae",
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+ "9": "rock"
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+ "jazz": "5",
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+ "metal": "6",
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+ "pop": "7",
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+ "reggae": "8",
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+ "rock": "9"
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "max_length": 1024,
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+ "model_type": "audio-spectrogram-transformer",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "num_mel_bins": 128,
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+ "patch_size": 16,
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+ "problem_type": "single_label_classification",
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+ "qkv_bias": true,
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+ "time_stride": 10,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.42.4"
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+ }
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