metadata
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
audio-commands
This model is a fine-tuned version of 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