---
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
model-index:
- name: whisper-large-v2-finetuning
  results: []
---

<!-- 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-large-v2-finetuning

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.1803
- eval_wer: 14.9238
- eval_runtime: 3860.013
- eval_samples_per_second: 2.453
- eval_steps_per_second: 0.307
- epoch: 1.5267
- step: 3000

## 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: 16
- 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: 8000
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.42.3
- Pytorch 2.2.1
- Datasets 2.20.0
- Tokenizers 0.19.1