---
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-v3-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-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: 0.0573
- Wer: 15.7807

## 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: 12500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.0031        | 8.33  | 1000  | 0.0372          | 54.8342 |
| 0.0005        | 16.67 | 2000  | 0.0415          | 20.1519 |
| 0.0024        | 25.0  | 3000  | 0.0392          | 10.2102 |
| 0.0           | 33.33 | 4000  | 0.0469          | 18.6609 |
| 0.0           | 41.67 | 5000  | 0.0493          | 17.3180 |
| 0.0           | 50.0  | 6000  | 0.0511          | 16.8179 |
| 0.0           | 58.33 | 7000  | 0.0526          | 16.4753 |
| 0.0           | 66.67 | 8000  | 0.0538          | 16.5725 |
| 0.0           | 75.0  | 9000  | 0.0550          | 15.9983 |
| 0.0           | 83.33 | 10000 | 0.0560          | 15.7205 |
| 0.0           | 91.67 | 11000 | 0.0568          | 15.7159 |
| 0.0           | 100.0 | 12000 | 0.0573          | 15.7807 |


### Framework versions

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