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---
license: apache-2.0
tags:
- generated_from_trainer
base_model: openai/whisper-medium
datasets:
- generator
metrics:
- wer
model-index:
- name: whisper-medium-lug-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: 9.766162310866575
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/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
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