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---
license: apache-2.0
base_model: arun100/whisper-base-uk-1
tags:
- whisper-event
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Base Ukrainian
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: google/fleurs uk_ua
type: google/fleurs
config: uk_ua
split: test
args: uk_ua
metrics:
- name: Wer
type: wer
value: 33.562978427279056
---
<!-- 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 [arun100/whisper-base-uk-1](https://huggingface.co/arun100/whisper-base-uk-1) on the google/fleurs uk_ua dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4710
- Wer: 33.5630
## 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: 2.5e-07
- 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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2683 | 95.0 | 1000 | 0.4710 | 33.5630 |
| 0.142 | 190.0 | 2000 | 0.4714 | 33.8344 |
| 0.0871 | 285.0 | 3000 | 0.4782 | 33.9596 |
| 0.0656 | 380.0 | 4000 | 0.4830 | 33.7230 |
| 0.0595 | 476.0 | 5000 | 0.4847 | 33.7161 |
### Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0
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