metadata
language:
- id
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_12_0
metrics:
- wer
model-index:
- name: Whisper base ID - Augmented
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_12_0
type: mozilla-foundation/common_voice_12_0
config: id
split: test
args: id
metrics:
- name: Wer
type: wer
value: 11.20271950074837
Whisper base ID - Augmented
This model is a fine-tuned version of openai/whisper-base on the mozilla-foundation/common_voice_12_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2277
- Wer: 11.2027
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.5509 | 0.77 | 200 | 0.3243 | 13.8588 |
| 0.3844 | 1.54 | 400 | 0.2590 | 11.1782 |
| 0.259 | 2.31 | 600 | 0.2422 | 18.6813 |
| 0.1608 | 3.07 | 800 | 0.2361 | 11.6678 |
| 0.1205 | 3.84 | 1000 | 0.2277 | 11.2027 |
Framework versions
- Transformers 4.29.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2