---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- toigen
metrics:
- wer
model-index:
- name: whisper-medium-toigen-combined-model
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: toigen
      type: toigen
    metrics:
    - name: Wer
      type: wer
      value: 0.4497528830313015
---

<!-- 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-toigen-combined-model

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co./openai/whisper-medium) on the toigen dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6425
- Wer: 0.4498

## 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 3.9586        | 0.9467 | 200  | 0.8733          | 0.5994 |
| 2.4999        | 1.8899 | 400  | 0.6726          | 0.4648 |
| 1.7047        | 2.8331 | 600  | 0.6523          | 0.4585 |
| 0.9573        | 3.7763 | 800  | 0.6425          | 0.4498 |
| 0.4029        | 4.7195 | 1000 | 0.6657          | 0.4043 |
| 0.2311        | 5.6627 | 1200 | 0.6910          | 0.4187 |
| 0.1545        | 6.6059 | 1400 | 0.7208          | 0.3864 |


### Framework versions

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