---
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-medium.en
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: wme_30s_Static_atWall_1.3
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 17.0
      type: mozilla-foundation/common_voice_17_0
      args: 'config: en, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 27.526025719534598
---

<!-- 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. -->

# wme_30s_Static_atWall_1.3

This model is a fine-tuned version of [openai/whisper-medium.en](https://huggingface.co/openai/whisper-medium.en) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9007
- Wer: 27.5260

## 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: 4e-05
- train_batch_size: 48
- 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: 26
- training_steps: 264
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| No log        | 0      | 0    | 1.5148          | 34.2009 |
| 0.8009        | 0.1667 | 44   | 1.0184          | 32.0882 |
| 0.5762        | 0.3333 | 88   | 0.9739          | 29.8836 |
| 0.553         | 0.5    | 132  | 0.9501          | 32.0269 |
| 0.4237        | 1.0038 | 176  | 0.9252          | 29.4550 |
| 0.2473        | 1.1705 | 220  | 0.9069          | 30.1286 |
| 0.1507        | 1.3371 | 264  | 0.9007          | 27.5260 |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1