metadata
base_model: MIT/ast-finetuned-audioset-10-10-0.4593
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: AST-finetuned-on-shEMO_speech
results: []
AST-finetuned-on-shEMO_speech
This model is a fine-tuned version of MIT/ast-finetuned-audioset-10-10-0.4593 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6988
- Accuracy: 0.7967
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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.8657 | 1.0 | 75 | 0.7066 | 0.7867 |
| 0.6951 | 2.0 | 150 | 0.6622 | 0.7567 |
| 0.3368 | 3.0 | 225 | 0.5851 | 0.8433 |
| 0.1414 | 4.0 | 300 | 0.7233 | 0.79 |
| 0.1011 | 5.0 | 375 | 0.8763 | 0.7967 |
| 0.0438 | 6.0 | 450 | 0.9009 | 0.8067 |
| 0.0108 | 7.0 | 525 | 1.0540 | 0.83 |
| 0.0033 | 8.0 | 600 | 1.0177 | 0.81 |
| 0.0003 | 9.0 | 675 | 1.1074 | 0.84 |
| 0.0113 | 10.0 | 750 | 1.1107 | 0.8433 |
| 0.0002 | 11.0 | 825 | 1.1273 | 0.8367 |
| 0.0001 | 12.0 | 900 | 1.1634 | 0.8333 |
| 0.0001 | 13.0 | 975 | 1.1502 | 0.84 |
| 0.0045 | 14.0 | 1050 | 1.1541 | 0.84 |
| 0.0039 | 15.0 | 1125 | 1.1550 | 0.84 |
Framework versions
- Transformers 4.34.1
- Pytorch 1.12.0+cu116
- Datasets 2.14.6
- Tokenizers 0.14.1