---
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: whisper-base-finetuned-500v2
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: audiofolder
      type: audiofolder
      config: default
      split: test
      args: default
    metrics:
    - name: Wer
      type: wer
      value: 83.78378378378379
---

<!-- 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. -->

# whisper-base-finetuned-500v2

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0286
- Wer Ortho: 83.7838
- Wer: 83.7838

## 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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 500

### Training results

| Training Loss | Epoch    | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:--------:|:----:|:---------------:|:---------:|:-------:|
| 0.0004        | 33.3333  | 100  | 1.0012          | 81.0811   | 81.0811 |
| 0.0001        | 66.6667  | 200  | 1.0110          | 78.3784   | 78.3784 |
| 0.0001        | 100.0    | 300  | 1.0186          | 78.3784   | 78.3784 |
| 0.0           | 133.3333 | 400  | 1.0241          | 81.0811   | 81.0811 |
| 0.0           | 166.6667 | 500  | 1.0286          | 83.7838   | 83.7838 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1