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---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- BrainTheos/ojpl
metrics:
- wer
model-index:
- name: whisper-tiny-ln-ojpl-2
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: BrainTheos/ojpl
      type: BrainTheos/ojpl
      config: default
      split: train
      args: default
    metrics:
    - name: Wer
      type: wer
      value: 0.4351648351648352
---

<!-- 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-tiny-ln-ojpl-2

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the BrainTheos/ojpl dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2661
- Wer Ortho: 50.1855
- Wer: 0.4352

## 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: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 2000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 0.1767        | 11.36 | 500  | 0.9122          | 52.1142   | 0.4579 |
| 0.0191        | 22.73 | 1000 | 1.0786          | 53.7463   | 0.4538 |
| 0.0059        | 34.09 | 1500 | 1.1891          | 53.2641   | 0.4766 |
| 0.0019        | 45.45 | 2000 | 1.2661          | 50.1855   | 0.4352 |


### Framework versions

- Transformers 4.31.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3