---
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-v3-cit-do015-wd0-lr1e-06-NYC-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. -->

# whisper-large-v3-cit-do015-wd0-lr1e-06-NYC-1000

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: 0.5601
- Wer Ortho: 29.5461
- Wer: 21.9669

## 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-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: 300
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 1.0667        | 1.8692 | 100  | 0.7607          | 37.1700   | 28.4674 |
| 0.7153        | 3.7383 | 200  | 0.6157          | 32.8982   | 24.5167 |
| 0.5672        | 5.6075 | 300  | 0.5747          | 30.5251   | 22.3872 |
| 0.4809        | 7.4766 | 400  | 0.5630          | 29.4275   | 21.7428 |
| 0.428         | 9.3458 | 500  | 0.5601          | 29.5461   | 21.9669 |


### Framework versions

- Transformers 4.44.0
- Pytorch 1.13.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1