metadata
language:
- en
license: apache-2.0
base_model: openai/whisper-tiny.en
tags:
- generated_from_trainer
datasets:
- Dev372/Medical_STT_Dataset_1_0_check_training
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_0_check_training
args: 'split: test'
metrics:
- name: Wer
type: wer
value: 6.0845332094751505
English Whisper Model
This model is a fine-tuned version of openai/whisper-tiny.en on the Medical dataset. It achieves the following results on the evaluation set:
- Loss: 0.1019
- Wer: 6.0845
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: 1500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.8606 | 1.0101 | 100 | 1.6059 | 9.1965 |
| 1.0954 | 2.0202 | 200 | 1.0513 | 6.2935 |
| 0.6627 | 3.0303 | 300 | 0.6161 | 6.6187 |
| 0.1747 | 4.0404 | 400 | 0.1527 | 4.2034 |
| 0.0554 | 5.0505 | 500 | 0.0924 | 5.3182 |
| 0.028 | 6.0606 | 600 | 0.0819 | 4.0641 |
| 0.0132 | 7.0707 | 700 | 0.0835 | 5.6897 |
| 0.0085 | 8.0808 | 800 | 0.0913 | 5.5504 |
| 0.0056 | 9.0909 | 900 | 0.0932 | 5.8059 |
| 0.0043 | 10.1010 | 1000 | 0.0982 | 5.8059 |
| 0.0023 | 11.1111 | 1100 | 0.0990 | 5.8755 |
| 0.0016 | 12.1212 | 1200 | 0.1005 | 6.0149 |
| 0.0015 | 13.1313 | 1300 | 0.1015 | 6.0613 |
| 0.0016 | 14.1414 | 1400 | 0.1017 | 6.0613 |
| 0.0015 | 15.1515 | 1500 | 0.1019 | 6.0845 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1