---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- swagen
metrics:
- wer
model-index:
- name: whisper-medium-swagen-female-model
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: swagen
      type: swagen
    metrics:
    - name: Wer
      type: wer
      value: 0.33982266769468006
---

<!-- 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-swagen-female-model

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the swagen dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5405
- Wer: 0.3398

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- 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
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 1.4291        | 0.4700 | 200  | 0.8217          | 0.4967 |
| 0.9176        | 0.9401 | 400  | 0.6348          | 0.4266 |
| 0.5492        | 1.4089 | 600  | 0.5868          | 0.4094 |
| 0.6243        | 1.8790 | 800  | 0.5535          | 0.3275 |
| 0.2196        | 2.3478 | 1000 | 0.5643          | 0.3577 |
| 0.2211        | 2.8179 | 1200 | 0.5405          | 0.3398 |
| 0.0999        | 3.2867 | 1400 | 0.5826          | 0.3283 |
| 0.1111        | 3.7568 | 1600 | 0.5537          | 0.3277 |
| 0.0423        | 4.2256 | 1800 | 0.6012          | 0.3188 |


### Framework versions

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