whisper-tiny_en / README.md
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---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny_en
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: PolyAI/minds14
type: PolyAI/minds14
config: en-US
split: train
args: en-US
metrics:
- name: Wer
type: wer
value: 34.56072351421189
---
<!-- 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
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: 0.5991
- Wer Ortho: 36.0700
- Wer: 34.5607
## 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-06
- 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: 1000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 4.3106 | 0.89 | 25 | 4.5196 | 51.0094 | 36.6925 |
| 3.9031 | 1.79 | 50 | 3.5872 | 51.0094 | 37.0155 |
| 2.9832 | 2.68 | 75 | 2.8616 | 48.9906 | 36.7571 |
| 2.3893 | 3.57 | 100 | 2.3230 | 47.1063 | 37.0155 |
| 1.9074 | 4.46 | 125 | 1.8030 | 44.6837 | 36.8863 |
| 1.3515 | 5.36 | 150 | 1.3467 | 43.5397 | 37.1447 |
| 0.9984 | 6.25 | 175 | 0.9622 | 42.6649 | 37.0155 |
| 0.7155 | 7.14 | 200 | 0.7915 | 42.1265 | 37.1447 |
| 0.6152 | 8.04 | 225 | 0.7200 | 41.1844 | 37.1447 |
| 0.523 | 8.93 | 250 | 0.6814 | 40.9152 | 37.1447 |
| 0.4744 | 9.82 | 275 | 0.6561 | 39.2328 | 35.8527 |
| 0.4411 | 10.71 | 300 | 0.6371 | 40.4441 | 37.4031 |
| 0.3926 | 11.61 | 325 | 0.6194 | 37.5505 | 35.2067 |
| 0.3855 | 12.5 | 350 | 0.6111 | 37.2140 | 35.0775 |
| 0.3709 | 13.39 | 375 | 0.6012 | 37.3486 | 35.1421 |
| 0.3315 | 14.29 | 400 | 0.5963 | 37.3486 | 35.2713 |
| 0.3113 | 15.18 | 425 | 0.5892 | 37.2813 | 35.4005 |
| 0.3112 | 16.07 | 450 | 0.5849 | 37.3486 | 35.4005 |
| 0.2809 | 16.96 | 475 | 0.5827 | 36.6756 | 34.7545 |
| 0.2694 | 17.86 | 500 | 0.5778 | 36.8775 | 34.9483 |
| 0.236 | 18.75 | 525 | 0.5775 | 36.2046 | 34.2377 |
| 0.2512 | 19.64 | 550 | 0.5755 | 36.6756 | 34.6899 |
| 0.2154 | 20.54 | 575 | 0.5760 | 36.2046 | 34.3023 |
| 0.2174 | 21.43 | 600 | 0.5742 | 36.0027 | 34.1085 |
| 0.1923 | 22.32 | 625 | 0.5741 | 36.2046 | 34.3669 |
| 0.198 | 23.21 | 650 | 0.5731 | 36.1373 | 34.3669 |
| 0.1699 | 24.11 | 675 | 0.5757 | 36.2719 | 34.5607 |
| 0.1662 | 25.0 | 700 | 0.5768 | 36.6083 | 34.9483 |
| 0.1559 | 25.89 | 725 | 0.5762 | 36.8775 | 35.1421 |
| 0.141 | 26.79 | 750 | 0.5801 | 36.9448 | 35.2713 |
| 0.1318 | 27.68 | 775 | 0.5791 | 36.8775 | 35.2067 |
| 0.1342 | 28.57 | 800 | 0.5809 | 37.0794 | 35.2713 |
| 0.1179 | 29.46 | 825 | 0.5829 | 36.8775 | 35.0775 |
| 0.1111 | 30.36 | 850 | 0.5835 | 37.2140 | 35.4005 |
| 0.0993 | 31.25 | 875 | 0.5887 | 37.0794 | 35.4005 |
| 0.0956 | 32.14 | 900 | 0.5900 | 36.6756 | 35.0129 |
| 0.0886 | 33.04 | 925 | 0.5944 | 36.7429 | 35.0775 |
| 0.0811 | 33.93 | 950 | 0.5945 | 36.3392 | 34.6899 |
| 0.0748 | 34.82 | 975 | 0.6010 | 36.6083 | 35.0775 |
| 0.0662 | 35.71 | 1000 | 0.5991 | 36.0700 | 34.5607 |
### Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3