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

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: 0.7932
- Wer: 42.6353

## 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     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.8768        | 0.4292 | 100  | 0.4849          | 38.3799 |
| 0.5884        | 0.8584 | 200  | 0.4886          | 37.6625 |
| 0.4802        | 1.2876 | 300  | 0.4899          | 42.7189 |
| 0.4519        | 1.7167 | 400  | 0.5002          | 42.3724 |
| 0.4173        | 2.1459 | 500  | 0.5083          | 43.9228 |
| 0.3271        | 2.5751 | 600  | 0.5200          | 41.2447 |
| 0.3292        | 3.0043 | 700  | 0.5020          | 41.7533 |
| 0.1963        | 3.4335 | 800  | 0.5670          | 43.8933 |
| 0.2076        | 3.8627 | 900  | 0.5536          | 42.9842 |
| 0.1413        | 4.2918 | 1000 | 0.5866          | 42.1439 |
| 0.1194        | 4.7210 | 1100 | 0.6091          | 43.5739 |
| 0.0994        | 5.1502 | 1200 | 0.6991          | 42.6722 |
| 0.067         | 5.5794 | 1300 | 0.6573          | 44.6869 |
| 0.0699        | 6.0086 | 1400 | 0.6579          | 44.4363 |
| 0.0386        | 6.4378 | 1500 | 0.7268          | 46.2249 |
| 0.0414        | 6.8670 | 1600 | 0.7219          | 44.3527 |
| 0.0334        | 7.2961 | 1700 | 0.7521          | 45.5763 |
| 0.0308        | 7.7253 | 1800 | 0.7932          | 42.6353 |


### Framework versions

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