---
license: apache-2.0
base_model: openai/whisper-base
tags:
- audio-classification
- generated_from_trainer
datasets:
- superb
metrics:
- accuracy
model-index:
- name: superb_si_42
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: superb
      type: superb
      config: si
      split: validation
      args: si
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6013904982618772
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# superb_si_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: 1.7025
- Accuracy: 0.6014

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 5.4406        | 1.0   | 4324  | 5.5144          | 0.0424   |
| 3.6304        | 2.0   | 8648  | 3.8862          | 0.1867   |
| 2.6868        | 3.0   | 12972 | 2.9909          | 0.3292   |
| 1.9548        | 4.0   | 17296 | 2.6032          | 0.3889   |
| 1.5749        | 5.0   | 21620 | 2.2077          | 0.4778   |
| 1.3105        | 6.0   | 25944 | 2.0726          | 0.5194   |
| 1.1002        | 7.0   | 30268 | 1.9175          | 0.5511   |
| 0.9522        | 8.0   | 34592 | 1.7847          | 0.5899   |
| 0.8263        | 9.0   | 38916 | 1.7225          | 0.5936   |
| 0.7333        | 10.0  | 43240 | 1.7025          | 0.6014   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1