File size: 2,526 Bytes
9f90e1b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 |
---
library_name: transformers
license: bsd-3-clause
base_model: MIT/ast-finetuned-audioset-10-10-0.4593
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: revix_classifier
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. -->
# revix_classifier
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.
It achieves the following results on the evaluation set:
- Loss: 0.4733
- Accuracy: 0.9292
- Precision: 0.9492
- Recall: 0.9106
- F1: 0.9295
## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.4055 | 1.0 | 120 | 0.4456 | 0.8 | 0.7698 | 0.8699 | 0.8168 |
| 0.4578 | 2.0 | 240 | 0.4217 | 0.875 | 0.8345 | 0.9431 | 0.8855 |
| 0.2235 | 3.0 | 360 | 0.4959 | 0.85 | 0.9780 | 0.7236 | 0.8318 |
| 0.092 | 4.0 | 480 | 0.3820 | 0.9083 | 0.9391 | 0.8780 | 0.9076 |
| 0.2152 | 5.0 | 600 | 0.5537 | 0.8792 | 0.8615 | 0.9106 | 0.8854 |
| 0.0612 | 6.0 | 720 | 0.4747 | 0.9292 | 0.9417 | 0.9187 | 0.9300 |
| 0.0382 | 7.0 | 840 | 0.4424 | 0.925 | 0.9412 | 0.9106 | 0.9256 |
| 0.0015 | 8.0 | 960 | 0.4647 | 0.925 | 0.9646 | 0.8862 | 0.9237 |
| 0.0005 | 9.0 | 1080 | 0.4684 | 0.9292 | 0.9492 | 0.9106 | 0.9295 |
| 0.0006 | 10.0 | 1200 | 0.4733 | 0.9292 | 0.9492 | 0.9106 | 0.9295 |
### Framework versions
- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0
|