---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-v2-atco2-asr
  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-atco2-asr

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: 0.7915
- Wer: 18.7722

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 2800

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1333        | 3.57  | 100  | 0.5298          | 21.8861 |
| 0.0338        | 7.14  | 200  | 0.5430          | 18.8167 |
| 0.0132        | 10.71 | 300  | 0.5830          | 17.9270 |
| 0.0067        | 14.29 | 400  | 0.6011          | 17.6157 |
| 0.0009        | 17.86 | 500  | 0.6582          | 18.8167 |
| 0.0004        | 21.43 | 600  | 0.6743          | 18.7722 |
| 0.0003        | 25.0  | 700  | 0.6919          | 18.4609 |
| 0.0004        | 28.57 | 800  | 0.6943          | 26.6459 |
| 0.0004        | 32.14 | 900  | 0.7090          | 18.5053 |
| 0.0002        | 35.71 | 1000 | 0.7212          | 18.8167 |
| 0.0001        | 39.29 | 1100 | 0.7305          | 18.8612 |
| 0.0001        | 42.86 | 1200 | 0.7383          | 18.6388 |
| 0.0001        | 46.43 | 1300 | 0.7451          | 18.5498 |
| 0.0001        | 50.0  | 1400 | 0.7515          | 18.5498 |
| 0.0001        | 53.57 | 1500 | 0.7573          | 18.5498 |
| 0.0001        | 57.14 | 1600 | 0.7622          | 18.5943 |
| 0.0001        | 60.71 | 1700 | 0.7666          | 18.5943 |
| 0.0001        | 64.29 | 1800 | 0.7705          | 18.5498 |
| 0.0001        | 67.86 | 1900 | 0.7744          | 18.6833 |
| 0.0001        | 71.43 | 2000 | 0.7778          | 18.6833 |
| 0.0001        | 75.0  | 2100 | 0.7808          | 18.7278 |
| 0.0001        | 78.57 | 2200 | 0.7837          | 18.6833 |
| 0.0001        | 82.14 | 2300 | 0.7856          | 18.6388 |
| 0.0001        | 85.71 | 2400 | 0.7881          | 18.6833 |
| 0.0001        | 89.29 | 2500 | 0.7896          | 18.6388 |
| 0.0001        | 92.86 | 2600 | 0.7905          | 18.7278 |
| 0.0001        | 96.43 | 2700 | 0.7915          | 18.8167 |
| 0.0001        | 100.0 | 2800 | 0.7915          | 18.7722 |


### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3