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---

language:
- he
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- OverloadedOperator/tests-101
metrics:
- wer
model-index:
- name: Whisper Small He
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: TestDS
      type: OverloadedOperator/tests-101
      config: default
      split: validation
      args: 'config: he, split: validation'
    metrics:
    - name: Wer
      type: wer
      value: 0.0
---


<!-- 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 Small He

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the TestDS dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Wer: 0.0

## 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: 8

- 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: 4000

- mixed_precision_training: Native AMP



### Training results



| Training Loss | Epoch  | Step | Validation Loss | Wer |

|:-------------:|:------:|:----:|:---------------:|:---:|

| 0.0           | 1000.0 | 1000 | 0.0000          | 0.0 |

| 0.0           | 2000.0 | 2000 | 0.0000          | 0.0 |

| 0.0           | 3000.0 | 3000 | 0.0000          | 0.0 |

| 0.0           | 4000.0 | 4000 | 0.0000          | 0.0 |





### Framework versions



- Transformers 4.38.2

- Pytorch 2.2.1+cu121

- Datasets 2.18.0

- Tokenizers 0.15.0