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---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-en-US
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: PolyAI/minds14
type: PolyAI/minds14
config: en-US
split: train[450:]
args: en-US
metrics:
- name: Wer
type: wer
value: 0.34946871310507677
---
<!-- 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-en-US
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: 0.7334
- Wer Ortho: 0.3701
- Wer: 0.3495
## 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: 48
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- num_epochs: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 2.5445 | 1.0 | 10 | 2.4472 | 0.5379 | 0.3985 |
| 2.0492 | 2.0 | 20 | 1.8586 | 0.5287 | 0.3973 |
| 1.3657 | 3.0 | 30 | 1.1065 | 0.4867 | 0.4038 |
| 0.6326 | 4.0 | 40 | 0.5885 | 0.4769 | 0.4115 |
| 0.3984 | 5.0 | 50 | 0.5155 | 0.4399 | 0.3861 |
| 0.2907 | 6.0 | 60 | 0.4921 | 0.3849 | 0.3347 |
| 0.236 | 7.0 | 70 | 0.4864 | 0.3886 | 0.3459 |
| 0.14 | 8.0 | 80 | 0.4936 | 0.3677 | 0.3264 |
| 0.106 | 9.0 | 90 | 0.5082 | 0.3917 | 0.3518 |
| 0.0837 | 10.0 | 100 | 0.5316 | 0.3819 | 0.3347 |
| 0.0458 | 11.0 | 110 | 0.5475 | 0.3899 | 0.3489 |
| 0.0201 | 12.0 | 120 | 0.5706 | 0.3893 | 0.3536 |
| 0.0099 | 13.0 | 130 | 0.5851 | 0.3831 | 0.3495 |
| 0.0067 | 14.0 | 140 | 0.6010 | 0.3769 | 0.3489 |
| 0.0036 | 15.0 | 150 | 0.6196 | 0.3819 | 0.3506 |
| 0.0021 | 16.0 | 160 | 0.6377 | 0.3782 | 0.3530 |
| 0.0013 | 17.0 | 170 | 0.6539 | 0.3708 | 0.3453 |
| 0.0006 | 18.0 | 180 | 0.6831 | 0.3720 | 0.3506 |
| 0.0004 | 19.0 | 190 | 0.7018 | 0.3732 | 0.3512 |
| 0.0003 | 20.0 | 200 | 0.7334 | 0.3701 | 0.3495 |
### Framework versions
- Transformers 4.46.1
- Pytorch 2.3.1
- Datasets 3.0.2
- Tokenizers 0.20.1
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