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anand095
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ast-finetuned-custom

Audio Classification
Transformers
TensorBoard
Safetensors
audio-spectrogram-transformer
Generated from Trainer
Eval Results (legacy)
Model card Files
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anand095 commited on
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End of training

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Files changed (4) hide show
  1. README.md +17 -13
  2. model.safetensors +1 -1
  3. runs/Nov02_15-39-59_c348f76a6a2a/events.out.tfevents.1762098000.c348f76a6a2a.19.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -23,7 +23,7 @@ model-index:
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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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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -33,8 +33,8 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.3930
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- - Accuracy: 0.87
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 2e-05
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  - train_batch_size: 16
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  - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Use OptimizerNames.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: 0.15
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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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- | 1.4964 | 1.0 | 57 | 0.6520 | 0.79 |
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- | 0.4667 | 2.0 | 114 | 0.4928 | 0.82 |
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- | 0.217 | 3.0 | 171 | 0.4175 | 0.88 |
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- | 0.0613 | 4.0 | 228 | 0.3876 | 0.88 |
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- | 0.0441 | 5.0 | 285 | 0.3930 | 0.87 |
 
 
 
 
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.94
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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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  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: 0.2095
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+ - Accuracy: 0.94
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 5e-06
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  - train_batch_size: 16
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  - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Use OptimizerNames.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: 0.3
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+ - num_epochs: 10
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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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+ | 2.3629 | 1.0877 | 62 | 2.0026 | 0.38 |
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+ | 1.816 | 2.1754 | 124 | 1.0936 | 0.76 |
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+ | 1.0625 | 3.2632 | 186 | 0.5384 | 0.87 |
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+ | 0.5878 | 4.3509 | 248 | 0.3465 | 0.91 |
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+ | 0.2426 | 5.4386 | 310 | 0.3506 | 0.88 |
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+ | 0.1584 | 6.5263 | 372 | 0.2532 | 0.92 |
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+ | 0.1067 | 7.6140 | 434 | 0.2333 | 0.9 |
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+ | 0.0741 | 8.7018 | 496 | 0.2248 | 0.91 |
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+ | 0.0431 | 9.7895 | 558 | 0.2095 | 0.94 |
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  ### Framework versions
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