---
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: openai/whisper-large-v2
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_13_0
      type: common_voice_13_0
      config: es
      split: test
      args: es
    metrics:
    - name: Wer
      type: wer
      value: 5.022549830956459
---

<!-- 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-large-v2

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2657
- Wer: 5.0225

## 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: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 20000

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.0869        | 2.0   | 1000  | 0.1754          | 6.1516 |
| 0.0913        | 4.0   | 2000  | 0.1652          | 5.7500 |
| 0.051         | 6.0   | 3000  | 0.1643          | 5.7757 |
| 0.0391        | 8.0   | 4000  | 0.1881          | 5.6589 |
| 0.0104        | 10.0  | 5000  | 0.2026          | 5.6211 |
| 0.0806        | 12.01 | 6000  | 0.1741          | 5.7398 |
| 0.0077        | 14.01 | 7000  | 0.2119          | 5.6038 |
| 0.0357        | 16.01 | 8000  | 0.1776          | 5.6147 |
| 0.1087        | 18.01 | 9000  | 0.1868          | 5.5172 |
| 0.0401        | 20.01 | 10000 | 0.2014          | 5.4428 |
| 0.0334        | 22.01 | 11000 | 0.1751          | 5.2824 |
| 0.0071        | 24.01 | 12000 | 0.2295          | 5.2490 |
| 0.0374        | 26.01 | 13000 | 0.2098          | 5.2574 |
| 0.0023        | 28.01 | 14000 | 0.2498          | 5.0418 |
| 0.0025        | 30.01 | 15000 | 0.2311          | 4.9385 |
| 0.0006        | 32.01 | 16000 | 0.2544          | 4.8949 |
| 0.0009        | 34.02 | 17000 | 0.2691          | 5.1246 |
| 0.003         | 36.02 | 18000 | 0.2249          | 5.0277 |
| 0.0009        | 38.02 | 19000 | 0.2603          | 5.0373 |
| 0.0008        | 40.02 | 20000 | 0.2657          | 5.0225 |


### Framework versions

- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3