---
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-medium
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-medium"
  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: 15.908591518347615
---

<!-- 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-medium

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the FluencyBank Timestamped dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8983
- Wer: 15.9086
- Cer: 10.9154

## 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     |
|:-------------:|:--------:|:----:|:---------------:|:-------:|:-------:|
| 1.4549        | 11.6279  | 250  | 1.7186          | 11.7776 | 6.6503  |
| 1.4261        | 23.2558  | 500  | 1.7611          | 10.8548 | 6.2588  |
| 1.4204        | 34.8837  | 750  | 1.8104          | 10.7888 | 6.2679  |
| 1.4216        | 46.5116  | 1000 | 1.7901          | 10.9207 | 6.4819  |
| 1.4179        | 58.1395  | 1250 | 1.8390          | 10.9426 | 6.4637  |
| 1.4168        | 69.7674  | 1500 | 1.8682          | 15.7328 | 10.7515 |
| 1.4164        | 81.3953  | 1750 | 1.8841          | 15.9086 | 10.8517 |
| 1.4161        | 93.0233  | 2000 | 1.8941          | 15.8207 | 10.8790 |
| 1.416         | 104.6512 | 2250 | 1.8984          | 15.9525 | 10.9882 |
| 1.416         | 116.2791 | 2500 | 1.8983          | 15.9086 | 10.9154 |


### Framework versions

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