metadata
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- speech_commands
metrics:
- accuracy
model-index:
- name: whisper-tiny-finetuned-no-go-kws
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: Speech Commands[no, go]
type: speech_commands
config: v0.02
split: test
args: v0.02
metrics:
- name: Accuracy
type: accuracy
value: 0.990086741016109
whisper-tiny-finetuned-no-go-kws
This model is a fine-tuned version of openai/whisper-tiny on the Speech Commands[no, go] dataset. It achieves the following results on the evaluation set:
- Loss: 0.0842
- Accuracy: 0.9901
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: 8
- eval_batch_size: 8
- 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: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.33 | 1.0 | 780 | 0.0272 | 0.9938 |
| 0.0002 | 2.0 | 1560 | 0.0420 | 0.9876 |
| 0.0001 | 3.0 | 2340 | 0.0487 | 0.9913 |
| 0.0011 | 4.0 | 3120 | 0.0789 | 0.9802 |
| 0.0001 | 5.0 | 3900 | 0.0915 | 0.9851 |
| 0.0014 | 6.0 | 4680 | 0.1017 | 0.9839 |
| 0.0 | 7.0 | 5460 | 0.0993 | 0.9888 |
| 0.0 | 8.0 | 6240 | 0.0694 | 0.9913 |
| 0.0 | 9.0 | 7020 | 0.0760 | 0.9926 |
| 0.0 | 10.0 | 7800 | 0.0842 | 0.9901 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0