---
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: CA
  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. -->

# CA

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the 3309 CA-2024-11-28 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4321
- Wer Ortho: 23.2856
- Wer: 16.0797

## 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: 200
- training_steps: 1200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 0.785         | 0.5369 | 100  | 0.5298          | 29.2975   | 21.3801 |
| 0.546         | 1.0738 | 200  | 0.4648          | 26.4263   | 18.8952 |
| 0.4399        | 1.6107 | 300  | 0.4377          | 25.2369   | 18.2070 |
| 0.4172        | 2.1477 | 400  | 0.4270          | 24.0940   | 17.0450 |
| 0.3578        | 2.6846 | 500  | 0.4219          | 23.7409   | 17.0272 |
| 0.3183        | 3.2215 | 600  | 0.4265          | 23.7781   | 16.5803 |
| 0.2929        | 3.7584 | 700  | 0.4187          | 23.6480   | 16.8127 |
| 0.2635        | 4.2953 | 800  | 0.4248          | 23.8710   | 16.8037 |
| 0.2511        | 4.8322 | 900  | 0.4238          | 23.7502   | 16.7322 |
| 0.236         | 5.3691 | 1000 | 0.4302          | 23.7316   | 16.5088 |
| 0.2121        | 5.9060 | 1100 | 0.4312          | 23.5923   | 16.4015 |
| 0.2089        | 6.4430 | 1200 | 0.4321          | 23.2856   | 16.0797 |


### Framework versions

- Transformers 4.45.1
- Pytorch 1.13.1+cu117
- Datasets 3.0.1
- Tokenizers 0.20.0