---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: openai/whisper-large-v2
  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. -->

# 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 None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8022
- Wer: 20.0210

## 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
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0029        | 8.33  | 100  | 0.6650          | 19.2872 |
| 0.0005        | 16.67 | 200  | 0.7456          | 18.4486 |
| 0.0003        | 25.0  | 300  | 0.7798          | 19.4969 |
| 0.0002        | 33.33 | 400  | 0.7964          | 19.7065 |
| 0.0002        | 41.67 | 500  | 0.8022          | 20.0210 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.1
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2