---
license: apache-2.0
tags:
- generated_from_trainer
base_model: openai/whisper-medium
datasets:
- generator
metrics:
- wer
model-index:
- name: whisper-medium-ach-only
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: generator
      type: generator
      config: default
      split: train
      args: default
    metrics:
    - type: wer
      value: 21.152030217186024
      name: Wer
---

<!-- 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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/bakera-sunbird/huggingface/runs/rycj9ija)
# whisper-medium-ach-only

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3942
- Wer: 21.1520

## 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     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 1.1662        | 0.05    | 200  | 0.7062          | 47.0255 |
| 0.6014        | 1.0248  | 400  | 0.4606          | 32.9556 |
| 0.5638        | 1.0748  | 600  | 0.4021          | 27.2899 |
| 0.3677        | 2.0495  | 800  | 0.3736          | 24.3626 |
| 0.2711        | 3.0242  | 1000 | 0.3648          | 23.5127 |
| 0.2862        | 3.0743  | 1200 | 0.3402          | 23.7016 |
| 0.2023        | 4.049   | 1400 | 0.3665          | 22.4740 |
| 0.1166        | 5.0237  | 1600 | 0.4023          | 23.6072 |
| 0.1089        | 5.0738  | 1800 | 0.3871          | 22.5685 |
| 0.0859        | 6.0485  | 2000 | 0.3837          | 25.6846 |
| 0.0557        | 7.0232  | 2200 | 0.3942          | 21.1520 |
| 0.0572        | 7.0732  | 2400 | 0.3805          | 22.0963 |
| 0.0469        | 8.048   | 2600 | 0.3995          | 23.6072 |
| 0.0308        | 9.0228  | 2800 | 0.4057          | 21.5297 |
| 0.0288        | 9.0727  | 3000 | 0.3999          | 21.1520 |
| 0.0222        | 10.0475 | 3200 | 0.4121          | 21.7186 |
| 0.0239        | 11.0222 | 3400 | 0.4162          | 21.9075 |
| 0.024         | 11.0723 | 3600 | 0.4154          | 21.9075 |
| 0.0219        | 12.047  | 3800 | 0.4186          | 21.3409 |
| 0.0133        | 13.0218 | 4000 | 0.4173          | 21.1520 |


### Framework versions

- Transformers 4.41.0.dev0
- Pytorch 2.2.0
- Datasets 2.16.1
- Tokenizers 0.19.1