---
base_model: openai/whisper-large-v3
library_name: transformers
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: whisper-large-v3-genbed-f
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: BembaSpeech
      type: BembaSpeech
      config: en
      split: test
    metrics:
    - type: wer
      value: 21.76
      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. -->

# whisper-large-v3-genbed-f

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4613
- Wer: 28.2294

## 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: 1.75e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.4575        | 0.6605 | 250  | 0.5118          | 48.6061 |
| 0.3575        | 1.3210 | 500  | 0.4580          | 41.5408 |
| 0.3229        | 1.9815 | 750  | 0.3920          | 34.9542 |
| 0.1937        | 2.6420 | 1000 | 0.4103          | 33.1986 |
| 0.0955        | 3.3025 | 1250 | 0.4218          | 32.8368 |
| 0.0943        | 3.9630 | 1500 | 0.4120          | 31.6982 |
| 0.0346        | 4.6235 | 1750 | 0.4397          | 30.2724 |
| 0.0123        | 5.2840 | 2000 | 0.4604          | 28.8891 |
| 0.0132        | 5.9445 | 2250 | 0.4485          | 29.1658 |
| 0.0025        | 6.6050 | 2500 | 0.4613          | 28.2294 |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1