|
--- |
|
license: bsd-3-clause |
|
base_model: MIT/ast-finetuned-audioset-10-10-0.4593 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- speech_commands |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: AST_speechcommandsV2_final |
|
results: |
|
- task: |
|
name: Audio Classification |
|
type: audio-classification |
|
dataset: |
|
name: speech_commands |
|
type: speech_commands |
|
config: v0.02 |
|
split: test |
|
args: v0.02 |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.8889570552147239 |
|
--- |
|
|
|
<!-- 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_speechcommandsV2_final |
|
|
|
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 speech_commands dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4825 |
|
- Accuracy: 0.8890 |
|
|
|
## 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: 72 |
|
- eval_batch_size: 72 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 288 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.3557 | 1.0 | 294 | 0.7017 | 0.8354 | |
|
| 0.1948 | 2.0 | 589 | 0.6838 | 0.8397 | |
|
| 0.1219 | 3.0 | 884 | 0.5752 | 0.8699 | |
|
| 0.0704 | 4.0 | 1179 | 0.5554 | 0.8675 | |
|
| 0.0404 | 5.0 | 1473 | 0.5437 | 0.8663 | |
|
| 0.0136 | 6.0 | 1768 | 0.5247 | 0.8759 | |
|
| 0.0072 | 7.0 | 2063 | 0.5235 | 0.8759 | |
|
| 0.0026 | 8.0 | 2358 | 0.5035 | 0.8859 | |
|
| 0.0007 | 9.0 | 2652 | 0.4800 | 0.8896 | |
|
| 0.0005 | 9.97 | 2940 | 0.4825 | 0.8890 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.0 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.14.6 |
|
- Tokenizers 0.14.1 |
|
|
