File size: 1,914 Bytes
50a6bdc 4c1596f 50a6bdc 3737622 50a6bdc 3737622 50a6bdc 3737622 50a6bdc 3737622 50a6bdc 4c1596f 50a6bdc 3737622 50a6bdc |
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 |
---
license: bsd-3-clause
base_model: MIT/ast-finetuned-audioset-10-10-0.4593
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: ast-finetuned-audioset-10-10-0.4593-finetuned-AST
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. -->
# ast-finetuned-audioset-10-10-0.4593-finetuned-AST
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: 0.3787
- Accuracy: 0.9463
- F1: 0.9426
## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.7914 | 1.0 | 1467 | 0.5058 | 0.8788 | 0.8679 |
| 0.5962 | 2.0 | 2934 | 0.4318 | 0.9018 | 0.8941 |
| 0.0143 | 3.0 | 4401 | 0.4418 | 0.9233 | 0.9183 |
| 0.0002 | 4.0 | 5868 | 0.3996 | 0.9387 | 0.9342 |
| 0.0001 | 5.0 | 7335 | 0.3787 | 0.9463 | 0.9426 |
### Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
|