---
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- generator
metrics:
- wer
model-index:
- name: whisper-medium-lug-only
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: generator
      type: generator
      config: default
      split: train
      args: default
    metrics:
    - name: Wer
      type: wer
      value: 9.766162310866575
---

<!-- 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/rim7iyop)
# whisper-medium-lug-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: 0.1551
- Wer: 9.7662

## 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: 8000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 1.1474        | 0.025  | 200  | 0.7380          | 71.3893 |
| 0.7879        | 0.05   | 400  | 0.4461          | 44.7043 |
| 0.6541        | 0.075  | 600  | 0.3394          | 32.3246 |
| 0.5203        | 0.1    | 800  | 0.2949          | 26.5475 |
| 0.509         | 0.125  | 1000 | 0.2774          | 24.2091 |
| 0.4753        | 0.15   | 1200 | 0.2505          | 20.4952 |
| 0.4726        | 0.175  | 1400 | 0.2375          | 20.7703 |
| 0.4145        | 0.2    | 1600 | 0.2313          | 18.2944 |
| 0.418         | 0.225  | 1800 | 0.2265          | 18.8446 |
| 0.4032        | 0.25   | 2000 | 0.2267          | 18.7070 |
| 0.3797        | 0.275  | 2200 | 0.2184          | 16.2311 |
| 0.3773        | 0.3    | 2400 | 0.2084          | 14.4429 |
| 0.3497        | 0.325  | 2600 | 0.1993          | 15.2682 |
| 0.3657        | 0.35   | 2800 | 0.1951          | 15.4058 |
| 0.3686        | 0.375  | 3000 | 0.1882          | 13.2050 |
| 0.3363        | 0.4    | 3200 | 0.1848          | 14.3054 |
| 0.3286        | 0.425  | 3400 | 0.1769          | 13.8927 |
| 0.3193        | 0.45   | 3600 | 0.1786          | 12.5172 |
| 0.3352        | 0.475  | 3800 | 0.1758          | 11.9670 |
| 0.3182        | 0.5    | 4000 | 0.1737          | 13.3425 |
| 0.2967        | 0.525  | 4200 | 0.1699          | 12.9298 |
| 0.3078        | 0.55   | 4400 | 0.1719          | 12.3796 |
| 0.2788        | 0.575  | 4600 | 0.1663          | 12.2421 |
| 0.2302        | 1.0075 | 4800 | 0.1678          | 11.4168 |
| 0.2109        | 1.0325 | 5000 | 0.1696          | 11.1417 |
| 0.1932        | 1.0575 | 5200 | 0.1713          | 11.2792 |
| 0.2128        | 1.0825 | 5400 | 0.1663          | 12.6547 |
| 0.2269        | 1.1075 | 5600 | 0.1621          | 12.2421 |
| 0.2324        | 1.1325 | 5800 | 0.1581          | 11.2792 |
| 0.2083        | 1.1575 | 6000 | 0.1579          | 11.1417 |
| 0.2156        | 1.1825 | 6200 | 0.1543          | 10.4539 |
| 0.2113        | 1.2075 | 6400 | 0.1551          | 9.7662  |
| 0.2235        | 1.2325 | 6600 | 0.1550          | 10.5915 |
| 0.2137        | 1.2575 | 6800 | 0.1537          | 10.4539 |
| 0.1989        | 1.2825 | 7000 | 0.1536          | 9.9037  |
| 0.2014        | 1.3075 | 7200 | 0.1515          | 10.1788 |
| 0.2109        | 1.3325 | 7400 | 0.1488          | 10.3164 |
| 0.1975        | 1.3575 | 7600 | 0.1500          | 10.5915 |
| 0.1754        | 1.3825 | 7800 | 0.1494          | 10.0413 |
| 0.182         | 1.4075 | 8000 | 0.1487          | 10.0413 |


### Framework versions

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