---
base_model: distil-whisper/distil-large-v3
datasets:
- audiofolder
library_name: peft
license: mit
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: distil_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
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# distil_whisper-v3-LoRA-en_students_test_2

This model is a fine-tuned version of [distil-whisper/distil-large-v3](https://huggingface.co/distil-whisper/distil-large-v3) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6839
- Wer: 18.4361

## 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: 28
- eval_batch_size: 28
- 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     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 1.5189        | 0.4444 | 500  | 1.1913          | 25.9108 |
| 1.1727        | 0.8889 | 1000 | 0.9531          | 24.5396 |
| 1.1341        | 1.3333 | 1500 | 0.8688          | 22.2761 |
| 1.0152        | 1.7778 | 2000 | 0.8174          | 20.8792 |
| 1.0589        | 2.2222 | 2500 | 0.7855          | 20.7595 |
| 0.9793        | 2.6667 | 3000 | 0.7611          | 22.2846 |
| 0.9594        | 3.1111 | 3500 | 0.7442          | 20.3860 |
| 1.0031        | 3.5556 | 4000 | 0.7303          | 18.5045 |
| 0.9525        | 4.0    | 4500 | 0.7199          | 18.1054 |
| 0.8729        | 4.4444 | 5000 | 0.7105          | 19.3170 |
| 1.0031        | 4.8889 | 5500 | 0.7028          | 19.7446 |
| 0.9273        | 5.3333 | 6000 | 0.6966          | 19.7189 |
| 0.9174        | 5.7778 | 6500 | 0.6896          | 18.4475 |
| 0.8842        | 6.2222 | 7000 | 0.6839          | 18.4361 |


### Framework versions

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