|
--- |
|
library_name: transformers |
|
language: |
|
- ru |
|
license: apache-2.0 |
|
base_model: openai/whisper-small |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- mozilla-foundation/common_voice_11_0 |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Whisper Small Ru |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: Common Voice 11.0 |
|
type: mozilla-foundation/common_voice_11_0 |
|
config: ru |
|
split: test |
|
args: 'config: ru, split: test' |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 14.91770049819283 |
|
--- |
|
|
|
<!-- 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 Small Ru |
|
|
|
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1877 |
|
- Wer: 14.9177 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 500 |
|
- training_steps: 4000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:------:|:----:|:---------------:|:-------:| |
|
| 0.171 | 0.4924 | 1000 | 0.2239 | 18.2194 | |
|
| 0.164 | 0.9847 | 2000 | 0.1985 | 16.0716 | |
|
| 0.0697 | 1.4771 | 3000 | 0.1922 | 15.4696 | |
|
| 0.0715 | 1.9695 | 4000 | 0.1877 | 14.9177 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.45.1 |
|
- Pytorch 2.4.1+cu124 |
|
- Datasets 3.0.1 |
|
- Tokenizers 0.20.0 |
|
|
