---
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- stuttered-speech
- speech-recognition
- asr
- whisper
- disfluency
- fluencybank
- generated_from_trainer
datasets:
- arielcerdap/TimeStamped-Splits
metrics:
- wer
model-index:
- name: "Whisper fine-tuned on FluencyBank \u2014 openai/whisper-small"
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: FluencyBank Timestamped
      type: arielcerdap/TimeStamped-Splits
      args: 'split: test, target: verbatim'
    metrics:
    - name: Wer
      type: wer
      value: 14.722039112283014
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper fine-tuned on FluencyBank — openai/whisper-small

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the FluencyBank Timestamped dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9714
- Wer: 14.7220
- Cer: 8.4574

## 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: 8e-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 2500
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch    | Step | Validation Loss | Wer     | Cer     |
|:-------------:|:--------:|:----:|:---------------:|:-------:|:-------:|
| 1.5202        | 11.6279  | 250  | 1.7446          | 14.2167 | 10.7879 |
| 1.4329        | 23.2558  | 500  | 1.8143          | 13.4476 | 7.7609  |
| 1.4254        | 34.8837  | 750  | 1.8473          | 13.2938 | 7.7063  |
| 1.4211        | 46.5116  | 1000 | 1.9020          | 13.8651 | 7.8338  |
| 1.4201        | 58.1395  | 1250 | 1.9092          | 13.8211 | 7.8611  |
| 1.4189        | 69.7674  | 1500 | 1.9383          | 14.1727 | 8.1615  |
| 1.418         | 81.3953  | 1750 | 1.9574          | 14.3265 | 8.2161  |
| 1.4177        | 93.0233  | 2000 | 1.9669          | 14.5023 | 8.3572  |
| 1.4176        | 104.6512 | 2250 | 1.9709          | 14.5902 | 8.3663  |
| 1.4175        | 116.2791 | 2500 | 1.9714          | 14.7220 | 8.4574  |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.20.3