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--- |
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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: AST-finetuned-on-shEMO_speech |
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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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# AST-finetuned-on-shEMO_speech |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6988 |
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- Accuracy: 0.7967 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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: 15 |
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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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| 0.8657 | 1.0 | 75 | 0.7066 | 0.7867 | |
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| 0.6951 | 2.0 | 150 | 0.6622 | 0.7567 | |
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| 0.3368 | 3.0 | 225 | 0.5851 | 0.8433 | |
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| 0.1414 | 4.0 | 300 | 0.7233 | 0.79 | |
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| 0.1011 | 5.0 | 375 | 0.8763 | 0.7967 | |
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| 0.0438 | 6.0 | 450 | 0.9009 | 0.8067 | |
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| 0.0108 | 7.0 | 525 | 1.0540 | 0.83 | |
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| 0.0033 | 8.0 | 600 | 1.0177 | 0.81 | |
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| 0.0003 | 9.0 | 675 | 1.1074 | 0.84 | |
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| 0.0113 | 10.0 | 750 | 1.1107 | 0.8433 | |
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| 0.0002 | 11.0 | 825 | 1.1273 | 0.8367 | |
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| 0.0001 | 12.0 | 900 | 1.1634 | 0.8333 | |
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| 0.0001 | 13.0 | 975 | 1.1502 | 0.84 | |
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| 0.0045 | 14.0 | 1050 | 1.1541 | 0.84 | |
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| 0.0039 | 15.0 | 1125 | 1.1550 | 0.84 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 1.12.0+cu116 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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