---
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Sep26-Mixat-whisper-lg-3-transliteration
  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. -->

# Sep26-Mixat-whisper-lg-3-transliteration

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7321
- Wer: 40.6571

## 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
- gradient_accumulation_steps: 2
- 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: 500
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.7747        | 0.4292 | 100  | 0.4311          | 36.6994 |
| 0.4882        | 0.8584 | 200  | 0.4418          | 35.7241 |
| 0.3749        | 1.2876 | 300  | 0.4387          | 40.5617 |
| 0.3644        | 1.7167 | 400  | 0.4506          | 40.1608 |
| 0.3451        | 2.1459 | 500  | 0.4571          | 42.6225 |
| 0.2678        | 2.5751 | 600  | 0.4558          | 38.1490 |
| 0.2737        | 3.0043 | 700  | 0.4406          | 38.5621 |
| 0.1576        | 3.4335 | 800  | 0.4937          | 42.0456 |
| 0.1653        | 3.8627 | 900  | 0.4995          | 41.7987 |
| 0.1113        | 4.2918 | 1000 | 0.5667          | 41.4100 |
| 0.0957        | 4.7210 | 1100 | 0.5606          | 39.9237 |
| 0.0817        | 5.1502 | 1200 | 0.6160          | 41.6984 |
| 0.0534        | 5.5794 | 1300 | 0.6003          | 42.2313 |
| 0.0549        | 6.0086 | 1400 | 0.5908          | 40.9724 |
| 0.0315        | 6.4378 | 1500 | 0.6655          | 40.5031 |
| 0.0364        | 6.8670 | 1600 | 0.7179          | 43.4389 |
| 0.0278        | 7.2961 | 1700 | 0.6839          | 42.8009 |
| 0.0251        | 7.7253 | 1800 | 0.6803          | 42.9891 |
| 0.0228        | 8.1545 | 1900 | 0.7166          | 42.3047 |
| 0.0197        | 8.5837 | 2000 | 0.7321          | 40.6571 |


### Framework versions

- Transformers 4.43.4
- Pytorch 2.4.1
- Datasets 3.0.0
- Tokenizers 0.19.1