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---
license: apache-2.0
base_model: openai/whisper-small
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: 0.9848484848484849
---
<!-- 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-small](https://huggingface.co/openai/whisper-small) on the superb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0976
- Accuracy: 0.9848
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3599 | 1.0 | 1597 | 0.1546 | 0.9707 |
| 0.0819 | 2.0 | 3194 | 0.0998 | 0.9762 |
| 0.0635 | 3.0 | 4791 | 0.1049 | 0.9800 |
| 0.0437 | 4.0 | 6388 | 0.0905 | 0.9797 |
| 0.0411 | 5.0 | 7985 | 0.0898 | 0.9809 |
| 0.0283 | 6.0 | 9582 | 0.1006 | 0.9812 |
| 0.0229 | 7.0 | 11179 | 0.0976 | 0.9848 |
| 0.0186 | 8.0 | 12776 | 0.1143 | 0.9825 |
| 0.0094 | 9.0 | 14373 | 0.1136 | 0.9835 |
| 0.0066 | 10.0 | 15970 | 0.1172 | 0.9834 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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