metadata
language:
- uk
license: apache-2.0
base_model: openai/whisper-base
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Whisper Base Ukrainian
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_16_0 uk
type: mozilla-foundation/common_voice_16_0
config: uk
split: test
args: uk
metrics:
- name: Wer
type: wer
value: 35.94087806808066
Whisper Base Ukrainian
This model is a fine-tuned version of openai/whisper-base on the mozilla-foundation/common_voice_16_0 uk dataset. It achieves the following results on the evaluation set:
- Loss: 0.4984
- Wer: 35.9409
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-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.5338 | 3.01 | 1000 | 0.5985 | 42.0862 |
| 0.4086 | 6.02 | 2000 | 0.5545 | 39.8889 |
| 0.336 | 9.02 | 3000 | 0.5347 | 38.2399 |
| 0.3672 | 13.0 | 4000 | 0.5165 | 37.2395 |
| 0.3862 | 16.01 | 5000 | 0.5096 | 36.7576 |
| 0.3298 | 19.02 | 6000 | 0.5040 | 36.5556 |
| 0.297 | 22.03 | 7000 | 0.5040 | 36.3153 |
| 0.3006 | 26.0 | 8000 | 0.4985 | 36.0172 |
| 0.3429 | 29.01 | 9000 | 0.4984 | 35.9409 |
| 0.2978 | 32.02 | 10000 | 0.4978 | 35.9423 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0