README.md

---
language:
- he
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- Alex2575/heb_anna
metrics:
- wer
model-index:
- name: aleksis_heb_tiny
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: heb_anna
      type: Alex2575/heb_anna
    metrics:
    - name: Wer
      type: wer
      value: 8.471596527854082
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# aleksis_heb_tiny

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the heb_anna dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0918
- Wer Ortho: 8.4716
- Wer: 8.4716

## 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: 1
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 0.123         | 4.24  | 500  | 0.0918          | 8.4716    | 8.4716 |


### Framework versions

- Transformers 4.35.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1