|
--- |
|
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 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# Whisper Base Ukrainian |
|
|
|
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/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 |
|
|