---
library_name: peft
language:
- en
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- wft
- whisper
- automatic-speech-recognition
- audio
- speech
- generated_from_trainer
datasets:
- hf-internal-testing/librispeech_asr_dummy
metrics:
- wer
model-index:
- name: wft-test-model
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: hf-internal-testing/librispeech_asr_dummy
      type: hf-internal-testing/librispeech_asr_dummy
    metrics:
    - type: wer
      value: 65.4320987654321
      name: Wer
---

<!-- 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. -->

# wft-test-model

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the hf-internal-testing/librispeech_asr_dummy dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0315
- Wer: 65.4321
- Cer: 30.1947

## 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: 0.0005
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 1.8721        | 1.0   | 8    | 1.5609          | 74.0741 | 31.3264 |
| 0.8099        | 2.0   | 16   | 1.2784          | 69.6296 | 31.1453 |
| 0.3841        | 3.0   | 24   | 1.1096          | 75.3086 | 36.5776 |
| 0.1898        | 4.0   | 32   | 1.0460          | 68.6420 | 32.5939 |
| 0.1511        | 5.0   | 40   | 1.0315          | 65.4321 | 30.1947 |


### Framework versions

- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.5.0
- Datasets 3.0.2
- Tokenizers 0.20.1