---
language:
- hu
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper large-v2 CV18 Hu
  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 large-v2 CV18 Hu

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the fsicoli/common_voice_18_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3493
- Wer Ortho: 21.9936
- Wer: 16.0057

## 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: 5e-06
- 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: 250
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:-------:|
| 0.1543        | 0.1   | 500   | 0.3619          | 25.7695   | 21.5802 |
| 0.1336        | 0.2   | 1000  | 0.3661          | 26.4197   | 21.9212 |
| 0.1358        | 0.3   | 1500  | 0.3516          | 25.4414   | 20.7548 |
| 0.1165        | 0.39  | 2000  | 0.3431          | 25.3937   | 20.3601 |
| 0.0959        | 0.49  | 2500  | 0.3581          | 26.6345   | 20.4438 |
| 0.1045        | 0.59  | 3000  | 0.3427          | 25.9127   | 19.9653 |
| 0.099         | 0.69  | 3500  | 0.3380          | 25.3937   | 19.6902 |
| 0.1034        | 0.79  | 4000  | 0.3412          | 24.5765   | 19.0083 |
| 0.0919        | 0.89  | 4500  | 0.3370          | 25.0119   | 19.3672 |
| 0.077         | 0.99  | 5000  | 0.3295          | 24.5884   | 19.3433 |
| 0.0447        | 1.09  | 5500  | 0.3405          | 23.6220   | 17.5668 |
| 0.0435        | 1.18  | 6000  | 0.3364          | 23.2999   | 17.4353 |
| 0.0383        | 1.28  | 6500  | 0.3370          | 22.9957   | 17.4831 |
| 0.0388        | 1.38  | 7000  | 0.3391          | 22.9838   | 17.1123 |
| 0.0436        | 1.48  | 7500  | 0.3345          | 22.7332   | 17.6745 |
| 0.0466        | 1.58  | 8000  | 0.3327          | 23.6101   | 17.3994 |
| 0.0357        | 1.68  | 8500  | 0.3477          | 24.2961   | 17.8121 |
| 0.0417        | 1.78  | 9000  | 0.3259          | 22.8883   | 16.7115 |
| 0.0383        | 1.88  | 9500  | 0.3206          | 22.0055   | 16.5859 |
| 0.0381        | 1.97  | 10000 | 0.3425          | 23.1508   | 16.8192 |
| 0.0153        | 2.07  | 10500 | 0.3461          | 22.5304   | 16.9807 |
| 0.0158        | 2.17  | 11000 | 0.3467          | 22.8227   | 16.7115 |
| 0.0228        | 2.27  | 11500 | 0.3439          | 22.3276   | 16.4244 |
| 0.0231        | 2.37  | 12000 | 0.3581          | 23.3954   | 16.6756 |
| 0.0171        | 2.47  | 12500 | 0.3537          | 22.7094   | 16.4304 |
| 0.0188        | 2.57  | 13000 | 0.3503          | 22.4588   | 16.8072 |
| 0.0157        | 2.67  | 13500 | 0.3518          | 22.5245   | 16.3826 |
| 0.0154        | 2.76  | 14000 | 0.3534          | 22.2739   | 16.0715 |
| 0.0205        | 2.86  | 14500 | 0.3479          | 21.9399   | 16.0237 |
| 0.0164        | 2.96  | 15000 | 0.3493          | 21.9936   | 16.0057 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.3.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1