---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
datasets:
- cymen-arfor/25awr
metrics:
- wer
model-index:
- name: whisper-large-v2-ft-ca-25awr
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: cymen-arfor/25awr default
      type: cymen-arfor/25awr
      args: default
    metrics:
    - name: Wer
      type: wer
      value: 0.40249424956871765
---

<!-- 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-ft-ca-25awr

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the cymen-arfor/25awr default dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8440
- Wer: 0.4025

## 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: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.4138        | 1.6488 | 1000 | 0.5216          | 0.5082 |
| 0.1535        | 3.2976 | 2000 | 0.5362          | 0.4263 |
| 0.084         | 4.9464 | 3000 | 0.5920          | 0.4038 |
| 0.0185        | 6.5952 | 4000 | 0.7443          | 0.4076 |
| 0.0038        | 8.2440 | 5000 | 0.8440          | 0.4025 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3