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  2. pytorch_model.bin +1 -1
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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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: S2_M1_R1_AST_42783267
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+ results: []
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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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+ # S2_M1_R1_AST_42783267
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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 None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0063
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+ - Accuracy: 0.9987
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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: 3e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 64
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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: 5
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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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+ | 0.0012 | 1.0 | 231 | 0.0061 | 0.9987 |
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+ | 0.0006 | 2.0 | 463 | 0.0073 | 0.9987 |
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+ | 0.0006 | 3.0 | 694 | 0.0039 | 0.9974 |
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+ | 0.0 | 4.0 | 926 | 0.0117 | 0.9974 |
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+ | 0.0 | 4.99 | 1155 | 0.0063 | 0.9987 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.32.1
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+ - Pytorch 2.1.2
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+ - Datasets 2.16.1
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+ - Tokenizers 0.13.3
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