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

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: 0.1039
- Wer: 22.2698

## 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
- total_train_batch_size: 64
- 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: 250
- training_steps: 12644
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.049         | 1.97  | 250   | 0.0613          | 41.3521 |
| 0.0168        | 3.94  | 500   | 0.0656          | 25.3775 |
| 0.0076        | 5.91  | 750   | 0.0703          | 16.7505 |
| 0.0028        | 7.87  | 1000  | 0.0722          | 23.0540 |
| 0.001         | 9.84  | 1250  | 0.0727          | 21.6365 |
| 0.0008        | 11.81 | 1500  | 0.0728          | 24.0815 |
| 0.0012        | 13.78 | 1750  | 0.0712          | 36.9653 |
| 0.0025        | 15.75 | 2000  | 0.0701          | 21.1248 |
| 0.0005        | 17.72 | 2250  | 0.0745          | 10.2458 |
| 0.0006        | 19.69 | 2500  | 0.0781          | 26.3169 |
| 0.0013        | 21.65 | 2750  | 0.0760          | 15.4127 |
| 0.0073        | 23.62 | 3000  | 0.0790          | 85.4764 |
| 0.0038        | 25.59 | 3250  | 0.0724          | 44.4682 |
| 0.0003        | 27.56 | 3500  | 0.0772          | 37.4056 |
| 0.0003        | 29.53 | 3750  | 0.0778          | 31.2238 |
| 0.0           | 31.5  | 4000  | 0.0806          | 22.4040 |
| 0.0           | 33.46 | 4250  | 0.0831          | 20.6886 |
| 0.0           | 35.43 | 4500  | 0.0847          | 20.3322 |
| 0.0           | 37.4  | 4750  | 0.0860          | 20.7935 |
| 0.0           | 39.37 | 5000  | 0.0871          | 20.3657 |
| 0.0           | 41.34 | 5250  | 0.0880          | 20.5293 |
| 0.0           | 43.31 | 5500  | 0.0889          | 20.7977 |
| 0.0           | 45.28 | 5750  | 0.0898          | 20.4957 |
| 0.0           | 47.24 | 6000  | 0.0906          | 20.9612 |
| 0.0           | 49.21 | 6250  | 0.0914          | 20.8564 |
| 0.0           | 51.18 | 6500  | 0.0921          | 21.1919 |
| 0.0           | 53.15 | 6750  | 0.0928          | 20.7809 |
| 0.0           | 55.12 | 7000  | 0.0934          | 21.1793 |
| 0.0           | 57.09 | 7250  | 0.0941          | 21.2087 |
| 0.0           | 59.06 | 7500  | 0.0947          | 21.2255 |
| 0.0           | 61.02 | 7750  | 0.0953          | 21.4142 |
| 0.0           | 62.99 | 8000  | 0.0959          | 21.1961 |
| 0.0           | 64.96 | 8250  | 0.0966          | 21.1080 |
| 0.0           | 66.93 | 8500  | 0.0972          | 21.0955 |
| 0.0           | 68.9  | 8750  | 0.0978          | 21.4226 |
| 0.0           | 70.87 | 9000  | 0.0983          | 21.3681 |
| 0.0           | 72.83 | 9250  | 0.0988          | 21.6532 |
| 0.0           | 74.8  | 9500  | 0.0994          | 21.6155 |
| 0.0           | 76.77 | 9750  | 0.0999          | 21.5107 |
| 0.0           | 78.74 | 10000 | 0.1005          | 21.3974 |
| 0.0           | 80.71 | 10250 | 0.1010          | 21.6407 |
| 0.0           | 82.68 | 10500 | 0.1014          | 21.7120 |
| 0.0           | 84.65 | 10750 | 0.1019          | 21.8755 |
| 0.0           | 86.61 | 11000 | 0.1023          | 21.9510 |
| 0.0           | 88.58 | 11250 | 0.1027          | 21.9636 |
| 0.0           | 90.55 | 11500 | 0.1030          | 22.0223 |
| 0.0           | 92.52 | 11750 | 0.1033          | 22.0265 |
| 0.0           | 94.49 | 12000 | 0.1036          | 22.3536 |
| 0.0           | 96.46 | 12250 | 0.1038          | 22.3956 |
| 0.0           | 98.43 | 12500 | 0.1039          | 22.2698 |


### Framework versions

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