---
language:
- en
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: ./openai/whisper-large-v3-cit-do015-wd0-lr5e-06-1000
  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. -->

# ./openai/whisper-large-v3-cit-do015-wd0-lr5e-06-1000

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on the SF 1000 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4753
- Wer Ortho: 23.5867
- Wer: 12.4052

## 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: 5e-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| No log        | 0.4444 | 25   | 1.1494          | 33.5283   | 21.6616 |
| 1.2689        | 0.8889 | 50   | 0.6362          | 28.0702   | 14.9090 |
| 1.2689        | 1.3333 | 75   | 0.5078          | 24.3275   | 12.2534 |
| 0.5452        | 1.7778 | 100  | 0.3860          | 23.1189   | 11.7602 |
| 0.5452        | 2.2222 | 125  | 0.3789          | 23.1969   | 11.1912 |
| 0.3251        | 2.6667 | 150  | 0.3691          | 24.0546   | 11.4568 |
| 0.3251        | 3.1111 | 175  | 0.3545          | 23.9376   | 11.5706 |
| 0.2441        | 3.5556 | 200  | 0.3701          | 25.3411   | 13.2018 |
| 0.2441        | 4.0    | 225  | 0.3564          | 21.4815   | 9.9393  |
| 0.1651        | 4.4444 | 250  | 0.3909          | 22.5731   | 10.3566 |
| 0.1651        | 4.8889 | 275  | 0.3708          | 24.6394   | 13.0121 |
| 0.1394        | 5.3333 | 300  | 0.3928          | 24.7563   | 13.2018 |
| 0.1394        | 5.7778 | 325  | 0.4097          | 24.6784   | 13.2018 |
| 0.1062        | 6.2222 | 350  | 0.4270          | 25.3021   | 13.4294 |
| 0.1062        | 6.6667 | 375  | 0.4133          | 24.2105   | 12.8225 |
| 0.0831        | 7.1111 | 400  | 0.4275          | 23.9766   | 13.0880 |
| 0.0831        | 7.5556 | 425  | 0.4592          | 23.1579   | 12.3293 |
| 0.065         | 8.0    | 450  | 0.4617          | 23.9376   | 12.5190 |
| 0.065         | 8.4444 | 475  | 0.4685          | 23.5088   | 12.4810 |
| 0.0558        | 8.8889 | 500  | 0.4753          | 23.5867   | 12.4052 |


### Framework versions

- Transformers 4.42.3
- Pytorch 1.13.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1