---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
datasets:
- nyagen
metrics:
- wer
model-index:
- name: whisper-large-v3-nyagen-balanced-model
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: nyagen
      type: nyagen
    metrics:
    - name: Wer
      type: wer
      value: 0.24026512013256007
---

<!-- 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-v3-nyagen-balanced-model

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the nyagen dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3155
- Wer: 0.2403

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 1.426         | 1.0756 | 200  | 0.4108          | 0.3070 |
| 0.6798        | 2.1511 | 400  | 0.3343          | 0.2867 |
| 0.3574        | 3.2267 | 600  | 0.3155          | 0.2403 |
| 0.2691        | 4.3023 | 800  | 0.3365          | 0.2158 |
| 0.1851        | 5.3779 | 1000 | 0.3159          | 0.2904 |
| 0.0715        | 6.4534 | 1200 | 0.3676          | 0.2084 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0