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---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: whisper-small-id
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_17_0 id
type: mozilla-foundation/common_voice_17_0
config: id
split: None
args: id
metrics:
- name: Wer
type: wer
value: 0.05902826117221217
---
<!-- 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-id
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_17_0 id dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0878
- Wer: 0.0590 (5.9%)
## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 20000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:-----:|:---------------:|:------:|
| 0.1875 | 0.8457 | 1000 | 0.1400 | 0.1099 |
| 0.0852 | 1.6913 | 2000 | 0.1043 | 0.0857 |
| 0.0387 | 2.5370 | 3000 | 0.0914 | 0.0757 |
| 0.0153 | 3.3827 | 4000 | 0.0860 | 0.0818 |
| 0.008 | 4.2283 | 5000 | 0.0878 | 0.0698 |
| 0.005 | 5.0740 | 6000 | 0.0878 | 0.0745 |
| 0.0033 | 5.9197 | 7000 | 0.0834 | 0.0651 |
| 0.0029 | 6.7653 | 8000 | 0.0815 | 0.0627 |
| 0.0014 | 7.6110 | 9000 | 0.0853 | 0.0627 |
| 0.0013 | 8.4567 | 10000 | 0.0861 | 0.0641 |
| 0.0005 | 9.3023 | 11000 | 0.0857 | 0.0633 |
| 0.0005 | 10.1480 | 12000 | 0.0856 | 0.0620 |
| 0.0007 | 10.9937 | 13000 | 0.0866 | 0.0605 |
| 0.0005 | 11.8393 | 14000 | 0.0871 | 0.0614 |
| 0.0002 | 12.6850 | 15000 | 0.0850 | 0.0596 |
| 0.0004 | 13.5307 | 16000 | 0.0849 | 0.0600 |
| 0.0001 | 14.3763 | 17000 | 0.0868 | 0.0592 |
| 0.0002 | 15.2220 | 18000 | 0.0873 | 0.0593 |
| 0.0001 | 16.0677 | 19000 | 0.0875 | 0.0585 |
| 0.0001 | 16.9133 | 20000 | 0.0878 | 0.0590 |
### Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
|