|
--- |
|
language: |
|
- sr |
|
license: apache-2.0 |
|
base_model: openai/whisper-large-v3 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- mozilla-foundation/common_voice_13_0 |
|
- google/fleurs |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Whisper Large v3 cmb |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: Common Voice 13 |
|
type: mozilla-foundation/common_voice_13_0 |
|
config: sr |
|
split: test |
|
args: sr |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 0.04148566463944396 |
|
--- |
|
|
|
<!-- 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 Large v3 cmb |
|
|
|
This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the Common Voice 13, Google Fleurs and juzne vesti dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1111 |
|
- Wer Ortho: 0.1339 |
|
- Wer: 0.0415 |
|
|
|
## Model description |
|
|
|
Dataset Juzne vesti is published by |
|
|
|
Rupnik, Peter and Ljubešić, Nikola, 2022,\ |
|
ASR training dataset for Serbian JuzneVesti-SR v1.0, Slovenian language resource repository CLARIN.SI, ISSN 2820-4042,\ |
|
http://hdl.handle.net/11356/1679. |
|
|
|
## 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: 2 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 8 |
|
- total_train_batch_size: 16 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 50 |
|
- training_steps: 1500 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:| |
|
| 0.2766 | 0.48 | 500 | 0.1350 | 0.1670 | 0.0595 | |
|
| 0.2813 | 0.95 | 1000 | 0.1134 | 0.1426 | 0.0491 | |
|
| 0.1858 | 1.43 | 1500 | 0.1111 | 0.1339 | 0.0415 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.2 |
|
- Pytorch 2.0.1+cu117 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.14.1 |
