---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large
tags:
- generated_from_trainer
datasets:
- deepinfinityai/29_lines_robust_dataset
metrics:
- wer
model-index:
- name: v5_Robust_Model
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: 29 Lines
      type: deepinfinityai/29_lines_robust_dataset
    metrics:
    - name: Wer
      type: wer
      value: 31.221719457013574
---

<!-- 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. -->

# v5_Robust_Model

This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the 29 Lines dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0001
- Wer: 31.2217

## 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: 4
- eval_batch_size: 8
- seed: 42
- 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: 50
- training_steps: 795
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 2.8614        | 1.25  | 50   | 0.2854          | 17.6471 |
| 0.1863        | 2.5   | 100  | 0.0002          | 25.7919 |
| 0.0009        | 3.75  | 150  | 0.0001          | 17.1946 |
| 0.0001        | 5.0   | 200  | 0.0001          | 19.0045 |
| 0.0001        | 6.25  | 250  | 0.0001          | 23.9819 |
| 0.0001        | 7.5   | 300  | 0.0001          | 25.7919 |
| 0.0001        | 8.75  | 350  | 0.0001          | 22.6244 |
| 0.0001        | 10.0  | 400  | 0.0001          | 24.8869 |
| 0.0001        | 11.25 | 450  | 0.0001          | 23.5294 |
| 0.0001        | 12.5  | 500  | 0.0001          | 27.1493 |
| 0.0001        | 13.75 | 550  | 0.0001          | 26.6968 |
| 0.0001        | 15.0  | 600  | 0.0001          | 28.5068 |
| 0.0001        | 16.25 | 650  | 0.0001          | 29.4118 |
| 0.0001        | 17.5  | 700  | 0.0001          | 29.8643 |
| 0.0001        | 18.75 | 750  | 0.0001          | 31.2217 |


### Framework versions

- Transformers 4.48.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0