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

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: 0.7130
- Wer: 43.1693

## 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: 16
- 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: 500
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.7784        | 0.4292 | 100  | 0.4158          | 34.8757 |
| 0.4942        | 0.8584 | 200  | 0.4306          | 33.8295 |
| 0.4017        | 1.2876 | 300  | 0.4313          | 38.3124 |
| 0.3677        | 1.7167 | 400  | 0.4539          | 39.1020 |
| 0.3498        | 2.1459 | 500  | 0.4611          | 41.6343 |
| 0.2632        | 2.5751 | 600  | 0.4645          | 37.8113 |
| 0.2701        | 3.0043 | 700  | 0.4461          | 37.3347 |
| 0.1499        | 3.4335 | 800  | 0.5147          | 40.4414 |
| 0.1596        | 3.8627 | 900  | 0.5218          | 41.5292 |
| 0.1073        | 4.2918 | 1000 | 0.5668          | 39.3977 |
| 0.0888        | 4.7210 | 1100 | 0.5665          | 39.4393 |
| 0.0738        | 5.1502 | 1200 | 0.6428          | 39.6104 |
| 0.0495        | 5.5794 | 1300 | 0.5914          | 41.9007 |
| 0.0512        | 6.0086 | 1400 | 0.6297          | 41.4950 |
| 0.0315        | 6.4378 | 1500 | 0.6753          | 44.4477 |
| 0.034         | 6.8670 | 1600 | 0.6906          | 38.4151 |
| 0.023         | 7.2961 | 1700 | 0.6998          | 40.0821 |
| 0.0251        | 7.7253 | 1800 | 0.7130          | 43.1693 |


### Framework versions

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