---
base_model: openai/whisper-large-v3
datasets:
- audiofolder
library_name: peft
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: whisper-v3-LoRA-en_students_test_2
  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-v3-LoRA-en_students_test_2

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3590
- Wer: 12.3268

## 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-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 100000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.9094        | 0.1270 | 500  | 0.6347          | 24.3686 |
| 0.5517        | 0.2541 | 1000 | 0.4835          | 18.0769 |
| 0.5364        | 0.3811 | 1500 | 0.4330          | 15.1149 |
| 0.5503        | 0.5081 | 2000 | 0.4113          | 13.6524 |
| 0.6521        | 0.6352 | 2500 | 0.3987          | 13.5897 |
| 0.6044        | 0.7622 | 3000 | 0.3912          | 13.0538 |
| 0.5487        | 0.8892 | 3500 | 0.3835          | 12.6119 |
| 0.5297        | 1.0163 | 4000 | 0.3791          | 12.4408 |
| 0.46          | 1.1433 | 4500 | 0.3751          | 12.3525 |
| 0.4947        | 1.2703 | 5000 | 0.3721          | 12.1415 |
| 0.524         | 1.3974 | 5500 | 0.3682          | 13.0139 |
| 0.4743        | 1.5244 | 6000 | 0.3649          | 13.3388 |
| 0.5338        | 1.6514 | 6500 | 0.3621          | 12.9397 |
| 0.5162        | 1.7785 | 7000 | 0.3597          | 13.3246 |
| 0.5004        | 1.9055 | 7500 | 0.3590          | 12.3268 |


### Framework versions

- PEFT 0.11.1
- Transformers 4.42.4
- Pytorch 2.1.0+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1