---
license: apache-2.0
tags:
- generated_from_trainer
base_model: openai/whisper-medium
datasets:
- generator
metrics:
- wer
model-index:
- name: whisper-medium-lug
  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: 61.62227602905569
      name: Wer
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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[<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/c6s8tlgq)
# whisper-medium-lug

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: 0.2943
- Wer: 61.6223

## 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      |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.9437        | 0.025   | 200  | 0.4902          | 427.9661 |
| 0.4586        | 1.0108  | 400  | 0.3298          | 150.3027 |
| 0.3741        | 1.0357  | 600  | 0.3337          | 143.5835 |
| 0.2659        | 2.0215  | 800  | 0.2871          | 109.6852 |
| 0.139         | 3.0072  | 1000 | 0.3437          | 131.9613 |
| 0.1734        | 3.0322  | 1200 | 0.3028          | 170.8838 |
| 0.1072        | 4.018   | 1400 | 0.2943          | 61.6223  |
| 0.0726        | 5.0038  | 1600 | 0.3438          | 114.7094 |
| 0.0751        | 5.0287  | 1800 | 0.3526          | 73.6683  |
| 0.0635        | 6.0145  | 2000 | 0.3629          | 159.7458 |
| 0.0554        | 7.0003  | 2200 | 0.3854          | 152.1186 |
| 0.0549        | 7.0252  | 2400 | 0.3751          | 98.5472  |
| 0.0283        | 8.011   | 2600 | 0.3190          | 89.2857  |
| 0.0349        | 8.036   | 2800 | 0.3452          | 155.5085 |
| 0.0379        | 9.0218  | 3000 | 0.3780          | 109.7458 |
| 0.0316        | 10.0075 | 3200 | 0.3880          | 101.4528 |
| 0.0232        | 10.0325 | 3400 | 0.4144          | 67.7966  |
| 0.0246        | 11.0183 | 3600 | 0.3820          | 71.0654  |
| 0.0192        | 12.004  | 3800 | 0.4022          | 107.6877 |
| 0.0195        | 12.029  | 4000 | 0.4276          | 126.9976 |
| 0.013         | 13.0147 | 4200 | 0.4128          | 115.3753 |
| 0.0154        | 14.0005 | 4400 | 0.4371          | 126.6949 |
| 0.0109        | 14.0255 | 4600 | 0.4213          | 142.2518 |
| 0.0133        | 15.0113 | 4800 | 0.4075          | 170.1574 |
| 0.011         | 15.0363 | 5000 | 0.4454          | 116.1622 |
| 0.0104        | 16.022  | 5200 | 0.3950          | 79.5400  |
| 0.0079        | 17.0078 | 5400 | 0.4330          | 109.2010 |
| 0.0083        | 17.0328 | 5600 | 0.4308          | 137.5303 |
| 0.0064        | 18.0185 | 5800 | 0.4178          | 96.2470  |
| 0.0057        | 19.0042 | 6000 | 0.4104          | 99.7579  |
| 0.0076        | 19.0293 | 6200 | 0.4132          | 117.0702 |
| 0.0062        | 20.015  | 6400 | 0.4404          | 146.2470 |
| 0.0035        | 21.0008 | 6600 | 0.4488          | 128.4504 |
| 0.0045        | 21.0257 | 6800 | 0.4415          | 91.0412  |
| 0.0043        | 22.0115 | 7000 | 0.4477          | 89.5884  |
| 0.0038        | 22.0365 | 7200 | 0.4550          | 82.5666  |
| 0.0028        | 23.0222 | 7400 | 0.4451          | 77.4213  |
| 0.003         | 24.008  | 7600 | 0.4424          | 78.5109  |
| 0.0033        | 24.033  | 7800 | 0.4448          | 73.4867  |
| 0.0041        | 25.0188 | 8000 | 0.4455          | 86.4407  |


### Framework versions

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