transformers tensorboard safetensors whisper automatic-speech-recognition whisper-event generated_from_trainer dataset:rishabhjain16/kaggle_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/kaggle_albanian
metrics:
- wer
model-index:
- name: Whisper large V3 to Kaggle Albanian
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: rishabhjain16/kaggle_albanian default
      type: rishabhjain16/kaggle_albanian
    metrics:
    - name: Wer
      type: wer
      value: 23.81094676029683
---

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# Whisper large V3 to Kaggle Albanian

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the rishabhjain16/kaggle_albanian default dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3189
- Wer: 23.8109

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2778        | 0.1   | 500  | 0.4945          | 36.9839 |
| 0.4343        | 0.2   | 1000 | 0.4290          | 35.1835 |
| 0.3523        | 0.3   | 1500 | 0.3780          | 30.6514 |
| 0.3833        | 0.4   | 2000 | 0.3436          | 28.0318 |
| 0.2029        | 1.09  | 2500 | 0.3360          | 26.5128 |
| 0.1797        | 1.19  | 3000 | 0.3351          | 25.8927 |
| 0.1687        | 1.29  | 3500 | 0.3249          | 25.8628 |
| 0.1603        | 1.39  | 4000 | 0.3089          | 23.9877 |
| 0.0762        | 2.08  | 4500 | 0.3345          | 24.5804 |
| 0.0676        | 2.18  | 5000 | 0.3189          | 23.8109 |


### Framework versions

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