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---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-us-ZA
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: PolyAI/minds14
type: PolyAI/minds14
config: en-US
split: train
args: en-US
metrics:
- name: Wer
type: wer
value: 0.27835051546391754
---
<!-- 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/soundofai/huggingface-audio-course-unit5-handson-af/runs/ym0ygfa9)
# whisper-tiny-us-ZA
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6915
- Wer Ortho: 0.2821
- Wer: 0.2784
## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 5
- training_steps: 2000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|
| 0.3413 | 3.125 | 100 | 0.4281 | 0.2727 | 0.2474 |
| 0.0659 | 6.25 | 200 | 0.4672 | 0.2754 | 0.2526 |
| 0.0076 | 9.375 | 300 | 0.5252 | 0.3035 | 0.2899 |
| 0.0019 | 12.5 | 400 | 0.5568 | 0.2874 | 0.2758 |
| 0.0009 | 15.625 | 500 | 0.5804 | 0.2901 | 0.2771 |
| 0.0006 | 18.75 | 600 | 0.5947 | 0.2861 | 0.2732 |
| 0.0005 | 21.875 | 700 | 0.6062 | 0.2848 | 0.2745 |
| 0.0004 | 25.0 | 800 | 0.6170 | 0.2834 | 0.2745 |
| 0.0003 | 28.125 | 900 | 0.6261 | 0.2834 | 0.2745 |
| 0.0003 | 31.25 | 1000 | 0.6346 | 0.2781 | 0.2719 |
| 0.0002 | 34.375 | 1100 | 0.6423 | 0.2794 | 0.2732 |
| 0.0002 | 37.5 | 1200 | 0.6497 | 0.2794 | 0.2732 |
| 0.0002 | 40.625 | 1300 | 0.6563 | 0.2794 | 0.2732 |
| 0.0002 | 43.75 | 1400 | 0.6627 | 0.2794 | 0.2732 |
| 0.0001 | 46.875 | 1500 | 0.6680 | 0.2941 | 0.2874 |
| 0.0001 | 50.0 | 1600 | 0.6736 | 0.2874 | 0.2809 |
| 0.0001 | 53.125 | 1700 | 0.6781 | 0.2874 | 0.2809 |
| 0.0001 | 56.25 | 1800 | 0.6833 | 0.2874 | 0.2809 |
| 0.0001 | 59.375 | 1900 | 0.6876 | 0.2834 | 0.2796 |
| 0.0001 | 62.5 | 2000 | 0.6915 | 0.2821 | 0.2784 |
### Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.19.1
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