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---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: whisper-tiny-common_voice_17_0-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: 0.1807044410413476
---
<!-- 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-tiny-common_voice_17_0-id
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the mozilla-foundation/common_voice_17_0 id dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2000
- Wer: 0.1807
## 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: 8
- 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: 500
- training_steps: 20000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 0.4911 | 0.4229 | 1000 | 0.4546 | 0.3321 |
| 0.4078 | 0.8458 | 2000 | 0.3520 | 0.2807 |
| 0.2679 | 1.2688 | 3000 | 0.3050 | 0.2421 |
| 0.2423 | 1.6917 | 4000 | 0.2725 | 0.2217 |
| 0.169 | 2.1146 | 5000 | 0.2515 | 0.2184 |
| 0.1646 | 2.5375 | 6000 | 0.2377 | 0.2082 |
| 0.1731 | 2.9605 | 7000 | 0.2189 | 0.1911 |
| 0.1017 | 3.3834 | 8000 | 0.2135 | 0.1970 |
| 0.0985 | 3.8063 | 9000 | 0.2077 | 0.1819 |
| 0.0828 | 4.2292 | 10000 | 0.2070 | 0.1792 |
| 0.06 | 4.6521 | 11000 | 0.1991 | 0.1826 |
| 0.0629 | 5.0751 | 12000 | 0.2012 | 0.1918 |
| 0.0545 | 5.4980 | 13000 | 0.2017 | 0.1864 |
| 0.0392 | 5.9209 | 14000 | 0.1985 | 0.1910 |
| 0.0338 | 6.3438 | 15000 | 0.1989 | 0.1807 |
| 0.0312 | 6.7668 | 16000 | 0.1982 | 0.1945 |
| 0.0237 | 7.1897 | 17000 | 0.1998 | 0.1842 |
| 0.0223 | 7.6126 | 18000 | 0.1994 | 0.1800 |
| 0.0192 | 8.0355 | 19000 | 0.1993 | 0.1806 |
| 0.0158 | 8.4584 | 20000 | 0.2000 | 0.1807 |
### Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.1.0
- Datasets 2.19.1
- Tokenizers 0.19.1
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