---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- Ussen/swc-drc-kat
metrics:
- wer
model-index:
- name: whisper-medium-swc-drc-kat-1
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Ussen/swc-drc-kat
      type: Ussen/swc-drc-kat
      config: default
      split: train
      args: default
    metrics:
    - name: Wer
      type: wer
      value: 0.49379203310915676
---

<!-- 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-swc-drc-kat-1

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Ussen/swc-drc-kat dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9701
- Wer Ortho: 50.0388
- Wer: 0.4938

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 0.6769        | 2.96  | 1000 | 0.8341          | 51.2296   | 0.5072 |
| 0.365         | 5.93  | 2000 | 0.8083          | 49.3917   | 0.4876 |
| 0.165         | 8.89  | 3000 | 0.8806          | 51.3073   | 0.5067 |
| 0.059         | 11.85 | 4000 | 0.9701          | 50.0388   | 0.4938 |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.3
- Tokenizers 0.13.3