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---
language:
- dv
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Small Dv - Peter Gelderbloem
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 13
type: mozilla-foundation/common_voice_13_0
config: dv
split: None
metrics:
- name: Wer
type: wer
value: 11.249434920193343
---
<!-- 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 Small Dv - Peter Gelderbloem
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2863
- Wer Ortho: 57.7129
- Wer: 11.2494
## 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: 50
- training_steps: 4000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Wer Ortho |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|
| 0.1248 | 1.63 | 500 | 0.1684 | 12.9881 | 62.0447 |
| 0.0484 | 3.26 | 1000 | 0.1629 | 11.6493 | 58.6113 |
| 0.0315 | 4.89 | 1500 | 0.1878 | 11.7224 | 58.9386 |
| 0.0125 | 6.51 | 2000 | 0.2308 | 11.0895 | 57.2185 |
| 0.0058 | 8.14 | 2500 | 0.2671 | 11.0773 | 57.6224 |
| 0.0049 | 9.77 | 3000 | 0.2843 | 11.2564 | 57.6572 |
| 0.0033 | 11.4 | 3500 | 0.2845 | 11.0982 | 57.1558 |
| 0.0046 | 13.03 | 4000 | 0.2863 | 57.7129 | 11.2494 |
### Framework versions
- Transformers 4.31.0.dev0
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.12.1
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