---
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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7578
- Wer: 29.0480

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1323        | 3.57  | 100  | 0.5386          | 20.4626 |
| 0.0207        | 7.14  | 200  | 0.5952          | 40.3025 |
| 0.0125        | 10.71 | 300  | 0.5767          | 25.9342 |
| 0.0056        | 14.29 | 400  | 0.6133          | 20.6406 |
| 0.0022        | 17.86 | 500  | 0.6367          | 30.2936 |
| 0.0005        | 21.43 | 600  | 0.6670          | 21.6637 |
| 0.0002        | 25.0  | 700  | 0.6841          | 22.2420 |
| 0.0002        | 28.57 | 800  | 0.6948          | 23.4431 |
| 0.0001        | 32.14 | 900  | 0.7026          | 23.6210 |
| 0.0001        | 35.71 | 1000 | 0.7095          | 26.0676 |
| 0.0001        | 39.29 | 1100 | 0.7153          | 25.9786 |
| 0.0001        | 42.86 | 1200 | 0.7202          | 25.1335 |
| 0.0001        | 46.43 | 1300 | 0.7251          | 25.3559 |
| 0.0001        | 50.0  | 1400 | 0.7295          | 29.4929 |
| 0.0001        | 53.57 | 1500 | 0.7334          | 25.9786 |
| 0.0001        | 57.14 | 1600 | 0.7373          | 28.6032 |
| 0.0001        | 60.71 | 1700 | 0.7402          | 28.9146 |
| 0.0           | 64.29 | 1800 | 0.7427          | 29.4484 |
| 0.0001        | 67.86 | 1900 | 0.7461          | 29.4484 |
| 0.0           | 71.43 | 2000 | 0.7480          | 32.2509 |
| 0.0           | 75.0  | 2100 | 0.7505          | 32.2064 |
| 0.0001        | 78.57 | 2200 | 0.7524          | 32.2064 |
| 0.0           | 82.14 | 2300 | 0.7539          | 32.2509 |
| 0.0           | 85.71 | 2400 | 0.7549          | 32.3843 |
| 0.0           | 89.29 | 2500 | 0.7563          | 32.2954 |
| 0.0           | 92.86 | 2600 | 0.7573          | 32.3399 |
| 0.0           | 96.43 | 2700 | 0.7578          | 29.0480 |
| 0.0           | 100.0 | 2800 | 0.7578          | 29.0480 |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2