---
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-v3-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-v3-atco2-asr

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7695
- Wer: 17.0374

## 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1388        | 3.57  | 100  | 0.5488          | 20.1957 |
| 0.0313        | 7.14  | 200  | 0.5830          | 17.5712 |
| 0.0173        | 10.71 | 300  | 0.5898          | 20.4181 |
| 0.004         | 14.29 | 400  | 0.6201          | 16.3256 |
| 0.001         | 17.86 | 500  | 0.6543          | 18.4164 |
| 0.002         | 21.43 | 600  | 0.6499          | 17.8381 |
| 0.0003        | 25.0  | 700  | 0.6724          | 17.1263 |
| 0.0002        | 28.57 | 800  | 0.6890          | 16.9929 |
| 0.0002        | 32.14 | 900  | 0.7012          | 16.8594 |
| 0.0001        | 35.71 | 1000 | 0.7104          | 16.9484 |
| 0.0001        | 39.29 | 1100 | 0.7178          | 16.9039 |
| 0.0001        | 42.86 | 1200 | 0.7241          | 17.4377 |
| 0.0001        | 46.43 | 1300 | 0.7305          | 17.3488 |
| 0.0001        | 50.0  | 1400 | 0.7358          | 17.3043 |
| 0.0001        | 53.57 | 1500 | 0.7407          | 17.3043 |
| 0.0001        | 57.14 | 1600 | 0.7451          | 17.1263 |
| 0.0001        | 60.71 | 1700 | 0.7495          | 17.2598 |
| 0.0001        | 64.29 | 1800 | 0.7529          | 17.2153 |
| 0.0001        | 67.86 | 1900 | 0.7563          | 17.2598 |
| 0.0001        | 71.43 | 2000 | 0.7593          | 17.4377 |
| 0.0001        | 75.0  | 2100 | 0.7612          | 17.3932 |
| 0.0001        | 78.57 | 2200 | 0.7632          | 17.2598 |
| 0.0           | 82.14 | 2300 | 0.7651          | 17.1263 |
| 0.0           | 85.71 | 2400 | 0.7666          | 17.0819 |
| 0.0           | 89.29 | 2500 | 0.7681          | 17.0374 |
| 0.0           | 92.86 | 2600 | 0.7686          | 17.0374 |
| 0.0           | 96.43 | 2700 | 0.7695          | 17.1263 |
| 0.0           | 100.0 | 2800 | 0.7695          | 17.0374 |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.14.1