---
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_atMic_1.1
  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: 18.922229026331905
---

<!-- 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_atMic_1.1

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: 0.6879
- Wer: 18.9222

## 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: 44
- training_steps: 440
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| No log        | 0      | 0    | 1.1143          | 21.3411 |
| 0.5297        | 0.2    | 88   | 0.6960          | 20.5144 |
| 0.3945        | 1.0023 | 176  | 0.6817          | 19.6877 |
| 0.1416        | 1.2023 | 264  | 0.6822          | 19.8408 |
| 0.1121        | 2.0045 | 352  | 0.6823          | 19.2284 |
| 0.0366        | 2.2045 | 440  | 0.6879          | 18.9222 |


### Framework versions

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