---
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
model-index:
- name: wft-test-model
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 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:
- eval_loss: 0.1185
- eval_wer: 5.9055
- eval_cer: 83.2386
- eval_decode_time: 0.5299
- eval_wer_time: 0.0047
- eval_cer_time: 0.0030
- eval_runtime: 1.3526
- eval_samples_per_second: 7.393
- eval_steps_per_second: 1.479
- epoch: 5.05
- step: 100

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 100

### Framework versions

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