---
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: whisper-medium-en-cv-6.2
  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: 31.659522351500307
---

<!-- 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-en-cv-6.2

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: 1.1366
- Wer: 31.6595

## 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: 3e-05
- train_batch_size: 48
- eval_batch_size: 4
- 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: 750
- training_steps: 7500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| No log        | 0     | 0    | 2.4185          | 46.5401 |
| 0.6822        | 0.1   | 750  | 0.9972          | 36.9871 |
| 0.2058        | 1.1   | 1500 | 1.0039          | 48.4997 |
| 0.0635        | 2.1   | 2250 | 1.0966          | 42.9884 |
| 0.0275        | 3.1   | 3000 | 1.1136          | 35.3950 |
| 0.0149        | 4.1   | 3750 | 1.1359          | 33.1598 |
| 0.0075        | 5.1   | 4500 | 1.1148          | 37.3546 |
| 0.0043        | 6.1   | 5250 | 1.1232          | 33.9865 |
| 0.0008        | 7.1   | 6000 | 1.1331          | 35.3644 |
| 0.0005        | 8.1   | 6750 | 1.1354          | 31.4452 |
| 0.0004        | 9.1   | 7500 | 1.1366          | 31.6595 |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.1
- Tokenizers 0.21.1