File size: 2,086 Bytes
e5d931a |
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 |
---
license: bsd-3-clause
base_model: MIT/ast-finetuned-audioset-10-10-0.4593
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: exp_1715025412
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. -->
# exp_1715025412
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: 0.6403
- Accuracy: 0.8974
## 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: 12
- eval_batch_size: 12
- seed: 42
- gradient_accumulation_steps: 5
- total_train_batch_size: 60
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.5131 | 0.9856 | 41 | 0.4401 | 0.8157 |
| 0.2645 | 1.9952 | 83 | 0.3510 | 0.875 |
| 0.2224 | 2.9808 | 124 | 0.3333 | 0.8910 |
| 0.1223 | 3.9904 | 166 | 0.4310 | 0.8830 |
| 0.0721 | 5.0 | 208 | 0.5080 | 0.8830 |
| 0.0059 | 5.9856 | 249 | 0.6021 | 0.8910 |
| 0.001 | 6.9952 | 291 | 0.6082 | 0.8878 |
| 0.0004 | 7.9808 | 332 | 0.6385 | 0.8942 |
| 0.0002 | 8.9904 | 374 | 0.6386 | 0.8958 |
| 0.0003 | 9.8558 | 410 | 0.6403 | 0.8974 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
|