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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
- precision
- recall
model-index:
- name: whisper-base-oshiwambo-speech
results: []
---
<!-- 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. -->
# whisper-base-oshiwambo-speech
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on [meyabase/crowd-oshiwambo-speech-greetings](https://huggingface.co/datasets/meyabase/crowd-oshiwambo-speech-greetings) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0834
- Wer: 80.9524
- Cer: 58.9623
- Word Acc: 82.2917
- Sent Acc: 54.2857
- Precision: 0.5097
- Recall: 0.7524
- F1 Score: 0.6077
## 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: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 10000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Word Acc | Sent Acc | Precision | Recall | F1 Score |
|:-------------:|:-------:|:-----:|:---------------:|:-------:|:-------:|:--------:|:--------:|:---------:|:------:|:--------:|
| 0.0099 | 117.65 | 1000 | 0.0777 | 46.6667 | 31.6038 | 69.1358 | 11.4286 | 0.6914 | 0.5333 | 0.6022 |
| 0.0105 | 235.29 | 2000 | 0.0806 | 47.6190 | 33.2547 | 71.4286 | 11.4286 | 0.7143 | 0.5238 | 0.6044 |
| 0.0106 | 352.94 | 3000 | 0.0795 | 44.7619 | 34.6698 | 76.3158 | 25.7143 | 0.7632 | 0.5524 | 0.6409 |
| 0.0092 | 470.59 | 4000 | 0.0793 | 42.8571 | 35.8491 | 81.0811 | 31.4286 | 0.8108 | 0.5714 | 0.6704 |
| 0.0099 | 588.24 | 5000 | 0.0806 | 92.3810 | 69.8113 | 81.7073 | 42.8571 | 0.4752 | 0.6381 | 0.5447 |
| 0.0094 | 705.88 | 6000 | 0.0800 | 28.5714 | 22.1698 | 83.3333 | 48.5714 | 0.8333 | 0.7143 | 0.7692 |
| 0.0093 | 823.53 | 7000 | 0.0796 | 24.7619 | 16.2736 | 82.2917 | 54.2857 | 0.8229 | 0.7524 | 0.7861 |
| 0.0095 | 941.18 | 8000 | 0.0815 | 82.8571 | 59.1981 | 80.2083 | 51.4286 | 0.4968 | 0.7333 | 0.5923 |
| 0.01 | 1058.82 | 9000 | 0.0815 | 24.7619 | 16.5094 | 82.2917 | 54.2857 | 0.8229 | 0.7524 | 0.7861 |
| 0.0088 | 1176.47 | 10000 | 0.0834 | 80.9524 | 58.9623 | 82.2917 | 54.2857 | 0.5097 | 0.7524 | 0.6077 |
### Framework versions
- Transformers 4.30.0.dev0
- Pytorch 2.0.0
- Datasets 2.12.0
- Tokenizers 0.13.3
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