metadata
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-ashok
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: 0.35301353013530135
whisper-tiny-ashok
This model is a fine-tuned version of openai/whisper-tiny on the PolyAI/minds14 dataset. It achieves the following results on the evaluation set:
- Loss: 0.8440
- Wer Ortho: 34.6847
- Wer: 0.3530
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.0234 | 6.67 | 100 | 0.6639 | 34.2986 | 0.3383 |
| 0.003 | 13.33 | 200 | 0.7587 | 33.9768 | 0.3401 |
| 0.0005 | 20.0 | 300 | 0.7870 | 34.2342 | 0.3475 |
| 0.0003 | 26.67 | 400 | 0.8045 | 35.1351 | 0.3567 |
| 0.0002 | 33.33 | 500 | 0.8144 | 35.5856 | 0.3610 |
| 0.0001 | 40.0 | 600 | 0.8262 | 35.5212 | 0.3604 |
| 0.0001 | 46.67 | 700 | 0.8341 | 35.3282 | 0.3592 |
| 0.0001 | 53.33 | 800 | 0.8397 | 35.1995 | 0.3579 |
| 0.0001 | 60.0 | 900 | 0.8426 | 34.7490 | 0.3536 |
| 0.0001 | 66.67 | 1000 | 0.8440 | 34.6847 | 0.3530 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3