---
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: ./4607
  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. -->

# ./4607

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on the 4607 FULL-2024-09-26 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5059
- Wer Ortho: 28.4797
- Wer: 21.0751

## 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: 1400
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 0.9206        | 0.7715 | 200  | 0.6309          | 33.9104   | 25.9900 |
| 0.6533        | 1.5429 | 400  | 0.5581          | 30.2736   | 22.5910 |
| 0.5875        | 2.3144 | 600  | 0.5322          | 29.5128   | 22.8648 |
| 0.5351        | 3.0858 | 800  | 0.5176          | 29.3103   | 21.8431 |
| 0.5126        | 3.8573 | 1000 | 0.5112          | 28.7100   | 21.3222 |
| 0.4956        | 4.6287 | 1200 | 0.5063          | 28.6053   | 21.0751 |
| 0.4785        | 5.4002 | 1400 | 0.5059          | 28.4797   | 21.0751 |


### Framework versions

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