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

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the [ATCOSIM](https://huggingface.co/datasets/jlvdoorn/ATCOSIM) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0679
- Wer: 6.2234

## 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: 1000
- training_steps: 50000

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer     |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.0147        | 2.09   | 1000  | 0.0373          | 4.7972  |
| 0.0058        | 4.18   | 2000  | 0.0379          | 4.5934  |
| 0.0012        | 6.28   | 3000  | 0.0388          | 4.5425  |
| 0.0067        | 8.37   | 4000  | 0.0382          | 4.0470  |
| 0.0026        | 10.46  | 5000  | 0.0382          | 2.9959  |
| 0.0016        | 12.55  | 6000  | 0.0457          | 2.9496  |
| 0.0027        | 14.64  | 7000  | 0.0473          | 4.6305  |
| 0.001         | 16.74  | 8000  | 0.0419          | 3.2969  |
| 0.0011        | 18.83  | 9000  | 0.0424          | 4.4592  |
| 0.0013        | 20.92  | 10000 | 0.0432          | 5.8807  |
| 0.0019        | 23.01  | 11000 | 0.0454          | 3.7646  |
| 0.0004        | 25.1   | 12000 | 0.0443          | 9.5110  |
| 0.004         | 27.2   | 13000 | 0.0442          | 2.8385  |
| 0.0018        | 29.29  | 14000 | 0.0444          | 2.5282  |
| 0.0011        | 31.38  | 15000 | 0.0467          | 4.0980  |
| 0.0002        | 33.47  | 16000 | 0.0469          | 3.9128  |
| 0.003         | 35.56  | 17000 | 0.0454          | 4.7462  |
| 0.0001        | 37.66  | 18000 | 0.0459          | 3.1950  |
| 0.0006        | 39.75  | 19000 | 0.0451          | 2.6579  |
| 0.0014        | 41.84  | 20000 | 0.0464          | 1.6855  |
| 0.0           | 43.93  | 21000 | 0.0487          | 2.3106  |
| 0.0005        | 46.03  | 22000 | 0.0535          | 7.3717  |
| 0.0001        | 48.12  | 23000 | 0.0482          | 6.9411  |
| 0.0002        | 50.21  | 24000 | 0.0484          | 13.0580 |
| 0.0001        | 52.3   | 25000 | 0.0481          | 18.0219 |
| 0.0           | 54.39  | 26000 | 0.0523          | 14.7342 |
| 0.0           | 56.49  | 27000 | 0.0552          | 11.1132 |
| 0.0004        | 58.58  | 28000 | 0.0521          | 2.5190  |
| 0.0001        | 60.67  | 29000 | 0.0490          | 4.4036  |
| 0.0           | 62.76  | 30000 | 0.0497          | 2.8246  |
| 0.0           | 64.85  | 31000 | 0.0513          | 2.8755  |
| 0.0           | 66.95  | 32000 | 0.0526          | 2.9172  |
| 0.0           | 69.04  | 33000 | 0.0539          | 3.0098  |
| 0.0           | 71.13  | 34000 | 0.0552          | 3.0144  |
| 0.0           | 73.22  | 35000 | 0.0566          | 3.1209  |
| 0.0           | 75.31  | 36000 | 0.0580          | 3.2321  |
| 0.0           | 77.41  | 37000 | 0.0594          | 3.4729  |
| 0.0           | 79.5   | 38000 | 0.0607          | 3.6164  |
| 0.0           | 81.59  | 39000 | 0.0620          | 3.9035  |
| 0.0           | 83.68  | 40000 | 0.0632          | 4.0656  |
| 0.0           | 85.77  | 41000 | 0.0642          | 4.3202  |
| 0.0           | 87.87  | 42000 | 0.0651          | 4.4453  |
| 0.0           | 89.96  | 43000 | 0.0659          | 4.9361  |
| 0.0           | 92.05  | 44000 | 0.0664          | 5.2186  |
| 0.0           | 94.14  | 45000 | 0.0670          | 5.6029  |
| 0.0           | 96.23  | 46000 | 0.0673          | 5.7835  |
| 0.0           | 98.33  | 47000 | 0.0676          | 6.0520  |
| 0.0           | 100.42 | 48000 | 0.0678          | 6.1122  |
| 0.0           | 102.51 | 49000 | 0.0679          | 6.2141  |
| 0.0           | 104.6  | 50000 | 0.0679          | 6.2234  |


### Framework versions

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