---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- bsbigcgen
metrics:
- wer
model-index:
- name: whisper-medium-bsbigcgen-female-model
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: bsbigcgen
      type: bsbigcgen
    metrics:
    - name: Wer
      type: wer
      value: 0.47723480333730633
---

<!-- 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-medium-bsbigcgen-female-model

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the bsbigcgen dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6368
- Wer: 0.4772

## 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: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 3.47          | 0.6163 | 200  | 0.9274          | 0.6675 |
| 2.569         | 1.2311 | 400  | 0.7236          | 0.5511 |
| 2.5305        | 1.8475 | 600  | 0.6368          | 0.4772 |
| 1.4563        | 2.4622 | 800  | 0.6518          | 0.4937 |
| 0.6413        | 3.0770 | 1000 | 0.6892          | 0.4782 |
| 0.581         | 3.6934 | 1200 | 0.6935          | 0.4751 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0