---
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: 0.1248
- Wer: 4.7244
- Cer: 92.6847
- Decode Time: 0.5481
- Wer Time: 0.0069
- Cer Time: 0.0040

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|:--------:|:--------:|
| 2.4107        | 0.1   | 10   | 1.9892          | 303.5433 | 117.1875 | 0.5449      | 0.0307   | 0.0039   |
| 1.2109        | 1.01  | 20   | 1.1659          | 155.1181 | 91.2642  | 0.5278      | 0.0062   | 0.0036   |
| 0.8855        | 1.11  | 30   | 0.8104          | 30.7087  | 56.8182  | 0.4832      | 0.0069   | 0.0041   |
| 0.4367        | 2.02  | 40   | 0.6315          | 25.1969  | 74.5739  | 0.5295      | 0.0058   | 0.0034   |
| 0.4398        | 2.12  | 50   | 0.4566          | 17.3228  | 91.9744  | 0.6078      | 0.0055   | 0.0030   |
| 0.2291        | 3.03  | 60   | 0.3006          | 9.0551   | 100.7102 | 0.5659      | 0.0058   | 0.0031   |
| 0.2281        | 3.13  | 70   | 0.2144          | 7.4803   | 90.4830  | 0.5507      | 0.0046   | 0.0030   |
| 0.111         | 4.04  | 80   | 0.1736          | 5.9055   | 89.3466  | 0.6595      | 0.0063   | 0.0032   |
| 0.0695        | 4.14  | 90   | 0.1345          | 4.7244   | 87.9261  | 0.6369      | 0.0402   | 0.0182   |
| 0.0761        | 5.05  | 100  | 0.1248          | 4.7244   | 92.6847  | 0.5481      | 0.0069   | 0.0040   |


### Framework versions

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