Model save
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- pytorch_model.bin +1 -1
README.md
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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: S5_M1_f3_AST_42783290
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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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# S5_M1_f3_AST_42783290
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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: 0.0127
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- Accuracy: 0.9984
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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: 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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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.0059 | 1.0 | 368 | 0.0092 | 0.9976 |
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| 0.0001 | 2.0 | 737 | 0.0139 | 0.9984 |
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| 0.0072 | 3.0 | 1105 | 0.0037 | 0.9984 |
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| 0.0 | 4.0 | 1474 | 0.0135 | 0.9984 |
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| 0.0 | 4.99 | 1840 | 0.0127 | 0.9984 |
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### Framework versions
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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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pytorch_model.bin
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