---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- common_voice_22_0
metrics:
- wer
model-index:
- name: openai/whisper-base
  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: 14.127053891405774
---

<!-- 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-base

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the common_voice_22_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5965
- Wer: 14.1271

## 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: 128
- eval_batch_size: 64
- 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     |
|:-------------:|:--------:|:-----:|:---------------:|:-------:|
| 0.0041        | 21.6450  | 5000  | 0.3770          | 16.8402 |
| 0.0025        | 43.2900  | 10000 | 0.4045          | 16.4480 |
| 0.0034        | 64.9351  | 15000 | 0.4193          | 16.2587 |
| 0.0014        | 86.5801  | 20000 | 0.4449          | 15.8953 |
| 0.0012        | 108.2251 | 25000 | 0.4490          | 15.8251 |
| 0.0           | 129.8701 | 30000 | 0.4585          | 14.3882 |
| 0.0           | 151.5152 | 35000 | 0.4865          | 13.9656 |
| 0.0           | 173.1602 | 40000 | 0.5256          | 13.7763 |
| 0.0           | 194.8052 | 45000 | 0.5518          | 13.6419 |
| 0.0           | 216.4502 | 50000 | 0.5558          | 13.6461 |
| 0.0           | 238.0952 | 55000 | 0.5683          | 13.7171 |
| 0.0           | 259.7403 | 60000 | 0.5801          | 13.9259 |
| 0.0           | 281.3853 | 65000 | 0.5886          | 13.9631 |
| 0.0           | 303.0303 | 70000 | 0.5965          | 14.1271 |


### Framework versions

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