transformers tensorboard safetensors whisper automatic-speech-recognition whisper-event generated_from_trainer dataset:rishabhjain16/owr_cv_albanian base_model:openai/whisper-large-v3 license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- whisper-event
- generated_from_trainer
datasets:
- rishabhjain16/owr_cv_albanian
metrics:
- wer
model-index:
- name: Whisper large V3 to CV Albanian
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: rishabhjain16/owr_cv_albanian default
      type: rishabhjain16/owr_cv_albanian
    metrics:
    - name: Wer
      type: wer
      value: 29.735234215885946
---

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# Whisper large V3 to CV Albanian

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the rishabhjain16/owr_cv_albanian default dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7039
- Wer: 29.7352

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0341        | 9.0   | 500  | 0.5451          | 34.7454 |
| 0.0107        | 18.01 | 1000 | 0.5565          | 31.4868 |
| 0.0012        | 27.01 | 1500 | 0.5967          | 30.5092 |
| 0.0001        | 37.0  | 2000 | 0.6311          | 30.7128 |
| 0.0001        | 46.0  | 2500 | 0.6630          | 30.0611 |
| 0.0           | 55.01 | 3000 | 0.6787          | 29.8167 |
| 0.0           | 64.01 | 3500 | 0.6894          | 29.6538 |
| 0.0           | 74.0  | 4000 | 0.6970          | 29.6538 |
| 0.0           | 83.0  | 4500 | 0.7019          | 29.6945 |
| 0.0           | 92.01 | 5000 | 0.7039          | 29.7352 |


### Framework versions

- Transformers 4.37.2
- Pytorch 1.14.0a0+44dac51
- Datasets 2.17.1
- Tokenizers 0.15.2
