| --- |
| license: bsd-3-clause |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: trainer |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # trainer |
|
|
| 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 an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3684 |
| - Accuracy: 0.9275 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 0.0001 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 8 |
| - total_train_batch_size: 64 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 50 |
| - training_steps: 1000 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 4.2624 | 2.0 | 50 | 0.3928 | 0.88 | |
| | 0.9069 | 4.0 | 100 | 0.3259 | 0.9025 | |
| | 0.9069 | 6.0 | 150 | 0.2775 | 0.93 | |
| | 0.0567 | 8.0 | 200 | 0.3220 | 0.9075 | |
| | 0.0567 | 10.0 | 250 | 0.3196 | 0.9075 | |
| | 0.0109 | 12.0 | 300 | 0.3644 | 0.9175 | |
| | 0.0109 | 14.0 | 350 | 0.3501 | 0.93 | |
| | 0.0138 | 16.0 | 400 | 0.3569 | 0.9275 | |
| | 0.0138 | 18.0 | 450 | 0.3700 | 0.9225 | |
| | 0.0006 | 20.0 | 500 | 0.3662 | 0.925 | |
| | 0.0006 | 22.0 | 550 | 0.3669 | 0.925 | |
| | 0.0002 | 24.0 | 600 | 0.3673 | 0.925 | |
| | 0.0002 | 26.0 | 650 | 0.3677 | 0.925 | |
| | 0.0002 | 28.0 | 700 | 0.3679 | 0.9275 | |
| | 0.0002 | 30.0 | 750 | 0.3680 | 0.9275 | |
| | 0.0002 | 32.0 | 800 | 0.3681 | 0.9275 | |
| | 0.0002 | 34.0 | 850 | 0.3684 | 0.9275 | |
| | 0.0002 | 36.0 | 900 | 0.3683 | 0.9275 | |
| | 0.0002 | 38.0 | 950 | 0.3684 | 0.9275 | |
| | 0.0002 | 40.0 | 1000 | 0.3684 | 0.9275 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.27.1 |
| - Pytorch 2.0.1+cu117 |
| - Datasets 2.13.1 |
| - Tokenizers 0.13.3 |
|
|
