---
library_name: transformers
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: 4.724409448818897
      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: 0.1218
- Wer: 4.7244
- Cer: 100.7102
- Decode Time: 0.5595
- Wer Time: 0.0060
- Cer Time: 0.0027

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|:--------:|:--------:|
| 2.4038        | 0.1   | 10   | 1.9871          | 299.6063 | 116.5483 | 0.5542      | 0.0112   | 0.0038   |
| 1.2202        | 1.01  | 20   | 1.1610          | 172.0472 | 91.6903  | 0.5178      | 0.0055   | 0.0028   |
| 0.8765        | 1.11  | 30   | 0.8079          | 31.8898  | 56.1080  | 0.4854      | 0.0051   | 0.0024   |
| 0.4415        | 2.02  | 40   | 0.6279          | 25.9843  | 82.5284  | 0.5218      | 0.0060   | 0.0028   |
| 0.4307        | 2.12  | 50   | 0.4509          | 16.9291  | 98.2955  | 0.5377      | 0.0056   | 0.0030   |
| 0.2363        | 3.03  | 60   | 0.2952          | 9.4488   | 102.9119 | 0.5310      | 0.0048   | 0.0027   |
| 0.2245        | 3.13  | 70   | 0.2046          | 7.4803   | 96.3778  | 0.5429      | 0.0056   | 0.0029   |
| 0.1053        | 4.04  | 80   | 0.1700          | 5.5118   | 96.4489  | 0.5306      | 0.0067   | 0.0028   |
| 0.0731        | 4.14  | 90   | 0.1320          | 4.7244   | 97.1591  | 0.5509      | 0.0050   | 0.0026   |
| 0.0782        | 5.05  | 100  | 0.1218          | 4.7244   | 100.7102 | 0.5595      | 0.0060   | 0.0027   |


### Framework versions

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