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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-asr-english
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: 0.31582054309327035
---
<!-- 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-asr-english
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:
- Wer Ortho: 0.3196
- Wer: 0.3158
- Loss: 0.5223
## 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: 4
- eval_batch_size: 4
- 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: 500
### Training results
| Training Loss | Epoch | Step | Wer Ortho | Wer | Validation Loss |
|:-------------:|:-----:|:----:|:---------:|:------:|:---------------:|
| 0.4862 | 0.89 | 100 | 0.3917 | 0.3719 | 0.5372 |
| 0.3213 | 1.79 | 200 | 0.3769 | 0.3571 | 0.4777 |
| 0.1822 | 2.68 | 300 | 0.3726 | 0.3589 | 0.4746 |
| 0.068 | 3.57 | 400 | 0.3276 | 0.3146 | 0.4819 |
| 0.0333 | 4.46 | 500 | 0.3196 | 0.3158 | 0.5223 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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