---
language:
- dv
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Large v3 DV - Alakxender
  results: []
pipeline_tag: automatic-speech-recognition
---

<!-- 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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/maxhar/whisper_largev3-dv-finetuning/runs/a8ygosbx)
# Whisper Large v3 DV - Alakxender

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4610
- Wer: 71.0345

## 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: 36
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer      |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.4644        | 0.9772  | 300  | 1.0654          | 203.9655 |
| 0.2384        | 1.9544  | 600  | 0.3342          | 84.8276  |
| 0.1481        | 2.9316  | 900  | 0.2715          | 78.7931  |
| 0.0975        | 2.9772  | 1200 | 0.2635          | 76.0345  |
| 0.0616        | 3.9544  | 1500 | 0.2841          | 73.1034  |
| 0.0399        | 4.9772  | 1800 | 0.3215          | 72.2414  |
| 0.0218        | 5.9772  | 2100 | 0.3881          | 73.7931  |
| 0.046         | 6.9772  | 2400 | 0.2772          | 74.1379  |
| 0.018         | 7.9544  | 2700 | 0.3344          | 71.3793  |
| 0.0067        | 8.9316  | 3000 | 0.3947          | 71.7241  |
| 0.0023        | 9.9088  | 3300 | 0.4246          | 72.5862  |
| 0.0008        | 10.8860 | 3600 | 0.4503          | 71.7241  |
| 0.0003        | 11.8632 | 3900 | 0.4610          | 71.0345  |


### Framework versions

- Transformers 4.41.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1