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---

license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: whisper-tiny-finetuned-100
  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: 113.51351351351352
---


<!-- 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-tiny-finetuned-100

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Wer Ortho: 108.1081
- Wer: 113.5135

## 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: 8

- eval_batch_size: 8

- seed: 42

- gradient_accumulation_steps: 2

- 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: 10

- training_steps: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer Ortho | Wer      |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:--------:|
| 0.0           | 16.6667 | 50   | nan             | 108.1081  | 113.5135 |
| 0.0           | 33.3333 | 100  | nan             | 108.1081  | 113.5135 |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1