---
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: whisper-medium-mix-pt
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_17_0
      type: common_voice_17_0
      config: pt
      split: test
      args: pt
    metrics:
    - name: Wer
      type: wer
      value: 7.122989865404904
---

<!-- 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-mix-pt

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1353
- Wer: 7.1230

## 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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.1116        | 0.2    | 1000 | 0.1570          | 8.5824 |
| 0.105         | 0.4    | 2000 | 0.1484          | 7.9398 |
| 0.0783        | 0.6    | 3000 | 0.1374          | 7.4475 |
| 0.1703        | 0.8    | 4000 | 0.1370          | 7.2413 |
| 0.0977        | 1.0622 | 5000 | 0.1353          | 7.1230 |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1