---
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- BrainTheos/ojpl
metrics:
- wer
model-index:
- name: whisper-medium-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: 0.29010989010989013
---

<!-- 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-medium-ln-ojpl-2

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the BrainTheos/ojpl dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1202
- Wer Ortho: 35.8309
- Wer: 0.2901

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- 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: 500
- training_steps: 4000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 0.0172        | 23.19 | 1000 | 0.9966          | 41.9139   | 0.3407 |
| 0.0053        | 46.38 | 2000 | 1.0716          | 37.0920   | 0.2996 |
| 0.0034        | 69.57 | 3000 | 1.1329          | 36.0163   | 0.2850 |
| 0.0021        | 92.75 | 4000 | 1.1202          | 35.8309   | 0.2901 |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3