transformers tensorboard safetensors whisper automatic-speech-recognition whisper-event generated_from_trainer uk dataset:mozilla-foundation/common_voice_16_0 base_model:openai/whisper-base license:apache-2.0 model-index endpoints_compatible region:us
---
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
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# 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
