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---
language:
- en
license: apache-2.0
base_model: openai/whisper-tiny.en
tags:
- generated_from_trainer
datasets:
- Dev372/Medical_STT_Dataset_1.1
metrics:
- wer
model-index:
- name: English Whisper Model
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Medical
type: Dev372/Medical_STT_Dataset_1.1
args: 'split: test'
metrics:
- name: Wer
type: wer
value: 6.5482216924132075
---
<!-- 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. -->
# English Whisper Model
This model is a fine-tuned version of [openai/whisper-tiny.en](https://huggingface.co/openai/whisper-tiny.en) on the Medical dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1566
- Wer: 6.5482
## 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: 18
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1100
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 1.8857 | 0.1554 | 55 | 1.6694 | 13.1520 |
| 1.3264 | 0.3107 | 110 | 1.0577 | 11.8358 |
| 0.9159 | 0.4661 | 165 | 0.8809 | 10.3857 |
| 0.8292 | 0.6215 | 220 | 0.7654 | 9.8893 |
| 0.641 | 0.7768 | 275 | 0.6364 | 9.2557 |
| 0.5445 | 0.9322 | 330 | 0.4931 | 8.6417 |
| 0.4072 | 1.0876 | 385 | 0.3397 | 8.2759 |
| 0.2378 | 1.2429 | 440 | 0.2414 | 8.1322 |
| 0.2109 | 1.3983 | 495 | 0.2116 | 7.6684 |
| 0.1641 | 1.5537 | 550 | 0.1940 | 7.6423 |
| 0.1498 | 1.7090 | 605 | 0.1819 | 7.1198 |
| 0.1445 | 1.8644 | 660 | 0.1752 | 6.8095 |
| 0.1349 | 2.0198 | 715 | 0.1679 | 6.7181 |
| 0.1032 | 2.1751 | 770 | 0.1661 | 6.7344 |
| 0.0898 | 2.3305 | 825 | 0.1632 | 6.8291 |
| 0.1032 | 2.4859 | 880 | 0.1606 | 6.7278 |
| 0.0845 | 2.6412 | 935 | 0.1592 | 6.7083 |
| 0.0958 | 2.7966 | 990 | 0.1578 | 6.5743 |
| 0.097 | 2.9520 | 1045 | 0.1570 | 6.5515 |
| 0.0689 | 3.1073 | 1100 | 0.1566 | 6.5482 |
### Framework versions
- Transformers 4.43.2
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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