transformers tensorboard safetensors whisper automatic-speech-recognition whisper-event generated_from_trainer dataset:rishabhjain16/kaggle_albanian base_model:openai/whisper-large-v2 license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- whisper-event
- generated_from_trainer
datasets:
- rishabhjain16/kaggle_albanian
metrics:
- wer
model-index:
- name: Whisper large V2 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: 25.160615568504408
---

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# Whisper large V2 to Kaggle Albanian

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the rishabhjain16/kaggle_albanian default dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3393
- Wer: 25.1606

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3422        | 0.1   | 500  | 0.5929          | 44.6536 |
| 0.4805        | 0.2   | 1000 | 0.4738          | 37.5890 |
| 0.3886        | 0.3   | 1500 | 0.4295          | 34.2173 |
| 0.3929        | 0.4   | 2000 | 0.3847          | 30.9552 |
| 0.2195        | 1.09  | 2500 | 0.3645          | 28.2136 |
| 0.1844        | 1.19  | 3000 | 0.3627          | 27.7056 |
| 0.1873        | 1.29  | 3500 | 0.3520          | 27.1403 |
| 0.1695        | 1.39  | 4000 | 0.3335          | 26.1816 |
| 0.089         | 2.08  | 4500 | 0.3623          | 26.1094 |
| 0.072         | 2.18  | 5000 | 0.3393          | 25.1606 |


### Framework versions

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