---
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-lr3e-06-FULL
  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-lr3e-06-FULL

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on the FULL dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5117
- Wer Ortho: 27.7362
- Wer: 18.6050

## 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: 3e-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     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 0.9582        | 0.4773 | 50   | 0.6479          | 34.9922   | 25.6303 |
| 0.6764        | 0.9547 | 100  | 0.5605          | 30.9901   | 21.5126 |
| 0.5263        | 1.4320 | 150  | 0.5337          | 29.3892   | 20.0168 |
| 0.5084        | 1.9093 | 200  | 0.5186          | 28.0842   | 19.1261 |
| 0.4226        | 2.3866 | 250  | 0.5132          | 27.9624   | 18.8571 |
| 0.4078        | 2.8640 | 300  | 0.5083          | 28.1538   | 19.0420 |
| 0.3775        | 3.3413 | 350  | 0.5083          | 28.3974   | 18.8403 |
| 0.3532        | 3.8186 | 400  | 0.5093          | 28.1538   | 18.6555 |
| 0.3359        | 4.2959 | 450  | 0.5098          | 27.7188   | 18.5210 |
| 0.3189        | 4.7733 | 500  | 0.5117          | 27.7362   | 18.6050 |


### Framework versions

- Transformers 4.42.4
- Pytorch 1.13.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1