---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- common_voice_22_0
metrics:
- wer
model-index:
- name: openai/whisper-medium
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_22_0
      type: common_voice_22_0
      config: eu
      split: test
      args: eu
    metrics:
    - name: Wer
      type: wer
      value: 11.199202109676111
---

<!-- 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. -->

# openai/whisper-medium

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the common_voice_22_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3322
- Wer: 11.1992

## 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: 3.75e-05
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.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: 100000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Wer     |
|:-------------:|:-------:|:-----:|:---------------:|:-------:|
| 0.0128        | 10.8225 | 5000  | 0.2586          | 10.4875 |
| 0.0073        | 21.6450 | 10000 | 0.2837          | 10.6540 |
| 0.0053        | 32.4675 | 15000 | 0.2982          | 10.8248 |
| 0.0039        | 43.2900 | 20000 | 0.3295          | 10.9025 |
| 0.0018        | 54.1126 | 25000 | 0.3297          | 10.7386 |
| 0.0044        | 64.9351 | 30000 | 0.3322          | 11.1992 |


### Framework versions

- Transformers 4.52.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1