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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-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
|