metadata
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- generated_from_trainer
datasets:
- speech_commands
metrics:
- accuracy
model-index:
- name: hubert-base-ls960-speech-commands
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: speech_commands
type: speech_commands
config: v0.02
split: None
args: v0.02
metrics:
- name: Accuracy
type: accuracy
value: 0.8057553956834532
hubert-base-ls960-speech-commands
This model is a fine-tuned version of facebook/hubert-base-ls960 on the speech_commands dataset. It achieves the following results on the evaluation set:
- Loss: 1.0829
- Accuracy: 0.8058
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: 5e-05
- train_batch_size: 48
- eval_batch_size: 48
- seed: 42
- 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.8285 | 1.0 | 824 | 1.9509 | 0.7167 |
| 0.5292 | 2.0 | 1648 | 1.3813 | 0.7909 |
| 0.3554 | 3.0 | 2472 | 1.1773 | 0.7941 |
| 0.2873 | 4.0 | 3296 | 1.2437 | 0.7981 |
| 0.2525 | 5.0 | 4120 | 1.2514 | 0.8004 |
| 0.2941 | 6.0 | 4944 | 1.2243 | 0.7995 |
| 0.1809 | 7.0 | 5768 | 1.1965 | 0.8008 |
| 0.2313 | 8.0 | 6592 | 1.0694 | 0.8022 |
| 0.1917 | 9.0 | 7416 | 1.0618 | 0.7995 |
| 0.1212 | 10.0 | 8240 | 1.0972 | 0.8026 |
| 0.185 | 11.0 | 9064 | 1.0868 | 0.8017 |
| 0.143 | 12.0 | 9888 | 1.1558 | 0.8031 |
| 0.2227 | 13.0 | 10712 | 1.0550 | 0.8040 |
| 0.1884 | 14.0 | 11536 | 1.0384 | 0.8022 |
| 0.1183 | 15.0 | 12360 | 1.0169 | 0.8035 |
| 0.1849 | 16.0 | 13184 | 1.0061 | 0.8035 |
| 0.141 | 17.0 | 14008 | 1.0337 | 0.8053 |
| 0.1328 | 18.0 | 14832 | 1.0829 | 0.8058 |
| 0.1238 | 19.0 | 15656 | 1.0576 | 0.8053 |
| 0.0932 | 20.0 | 16480 | 1.0641 | 0.8053 |
Framework versions
- Transformers 4.43.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1