---
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: 5.905511811023622
      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: 0.1185
- Wer: 5.9055
- Cer: 83.2386
- Decode Time: 0.5299
- Wer Time: 0.0047
- Cer Time: 0.0030

## 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      | Cer      | Decode Time | Wer Time | Cer Time |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|:--------:|:--------:|
| 2.4079        | 0.1   | 10   | 1.9885          | 312.2047 | 119.2472 | 0.5334      | 0.0169   | 0.0041   |
| 1.2303        | 1.01  | 20   | 1.1646          | 258.2677 | 100.0    | 0.5213      | 1.4057   | 0.0046   |
| 0.8667        | 1.11  | 30   | 0.8100          | 37.7953  | 52.3438  | 0.5008      | 0.0396   | 0.0045   |
| 0.4517        | 2.02  | 40   | 0.6337          | 40.9449  | 73.7926  | 0.5137      | 0.0217   | 0.0030   |
| 0.4352        | 2.12  | 50   | 0.4493          | 16.5354  | 88.1392  | 0.5203      | 0.0054   | 0.0032   |
| 0.2341        | 3.03  | 60   | 0.2922          | 8.2677   | 97.5852  | 0.5434      | 0.0060   | 0.0032   |
| 0.2233        | 3.13  | 70   | 0.2026          | 9.0551   | 83.5227  | 0.5359      | 0.0063   | 0.0033   |
| 0.1098        | 4.04  | 80   | 0.1665          | 5.9055   | 83.9489  | 0.5316      | 0.0056   | 0.0029   |
| 0.0678        | 4.14  | 90   | 0.1279          | 7.0866   | 81.1080  | 0.5388      | 0.0079   | 0.0038   |
| 0.078         | 5.05  | 100  | 0.1185          | 5.9055   | 83.2386  | 0.5299      | 0.0047   | 0.0030   |


### Framework versions

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