|
--- |
|
license: bsd-3-clause |
|
base_model: MIT/ast-finetuned-speech-commands-v2 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- speech_commands |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: audio-commands |
|
results: |
|
- task: |
|
name: Audio Classification |
|
type: audio-classification |
|
dataset: |
|
name: speech_commands |
|
type: speech_commands |
|
config: v0.03 |
|
split: test |
|
args: v0.03 |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.9256316218418907 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# audio-commands |
|
|
|
This model is a fine-tuned version of [MIT/ast-finetuned-speech-commands-v2](https://huggingface.co/MIT/ast-finetuned-speech-commands-v2) on the speech_commands dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3977 |
|
- Accuracy: 0.9256 |
|
|
|
## 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: 32 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 128 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 20 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
|
| 0.0581 | 1.0 | 663 | 0.4816 | 0.8975 | |
|
| 0.0454 | 2.0 | 1326 | 0.4184 | 0.9024 | |
|
| 0.0404 | 3.0 | 1989 | 0.4361 | 0.9010 | |
|
| 0.025 | 4.0 | 2653 | 0.4368 | 0.9016 | |
|
| 0.0169 | 5.0 | 3316 | 0.3692 | 0.9173 | |
|
| 0.0173 | 6.0 | 3979 | 0.4131 | 0.9173 | |
|
| 0.0096 | 7.0 | 4642 | 0.3800 | 0.9177 | |
|
| 0.0022 | 8.0 | 5306 | 0.3535 | 0.9264 | |
|
| 0.0031 | 9.0 | 5969 | 0.3241 | 0.9315 | |
|
| 0.0008 | 10.0 | 6632 | 0.3697 | 0.9236 | |
|
| 0.0002 | 11.0 | 7295 | 0.4189 | 0.9173 | |
|
| 0.001 | 12.0 | 7959 | 0.3206 | 0.9287 | |
|
| 0.0003 | 13.0 | 8622 | 0.3794 | 0.9205 | |
|
| 0.0003 | 14.0 | 9285 | 0.3999 | 0.9199 | |
|
| 0.0 | 15.0 | 9948 | 0.4002 | 0.9220 | |
|
| 0.0 | 16.0 | 10612 | 0.3896 | 0.9248 | |
|
| 0.0001 | 17.0 | 11275 | 0.3930 | 0.9248 | |
|
| 0.0 | 18.0 | 11938 | 0.3952 | 0.9254 | |
|
| 0.0 | 19.0 | 12601 | 0.3971 | 0.9254 | |
|
| 0.0 | 19.99 | 13260 | 0.3977 | 0.9256 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.2 |
|
- Pytorch 2.1.2+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|
