|
--- |
|
license: apache-2.0 |
|
base_model: openai/whisper-base |
|
tags: |
|
- audio-classification |
|
- generated_from_trainer |
|
datasets: |
|
- superb |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: superb_ks_42 |
|
results: |
|
- task: |
|
name: Audio Classification |
|
type: audio-classification |
|
dataset: |
|
name: superb |
|
type: superb |
|
config: ks |
|
split: validation |
|
args: ks |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.9833774639599883 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# superb_ks_42 |
|
|
|
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the superb dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1152 |
|
- Accuracy: 0.9834 |
|
|
|
## 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: 32 |
|
- eval_batch_size: 4 |
|
- 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 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
|
| 0.6909 | 1.0 | 1597 | 0.1572 | 0.9651 | |
|
| 0.0891 | 2.0 | 3194 | 0.1597 | 0.9660 | |
|
| 0.0676 | 3.0 | 4791 | 0.1304 | 0.9719 | |
|
| 0.0475 | 4.0 | 6388 | 0.0999 | 0.9796 | |
|
| 0.0433 | 5.0 | 7985 | 0.1079 | 0.9798 | |
|
| 0.0284 | 6.0 | 9582 | 0.1089 | 0.9803 | |
|
| 0.0236 | 7.0 | 11179 | 0.1162 | 0.9819 | |
|
| 0.0193 | 8.0 | 12776 | 0.1152 | 0.9834 | |
|
| 0.0111 | 9.0 | 14373 | 0.1272 | 0.9821 | |
|
| 0.0088 | 10.0 | 15970 | 0.1306 | 0.9826 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.40.1 |
|
- Pytorch 2.3.0+cu121 |
|
- Datasets 2.19.0 |
|
- Tokenizers 0.19.1 |
|
|