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---
base_model: openai/whisper-large-v3
datasets:
- mozilla-foundation/common_voice_11_0
language:
- th
library_name: peft
license: apache-2.0
metrics:
- wer
- ter
- chrf
- cer
- bleu
- suber
tags:
- generated_from_trainer
model-index:
- name: Whisper Large V3 Thai Lora - Magi Boss
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: th
split: None
args: 'config: th, split: validation'
metrics:
- type: wer
value: 0.8101
name: Wer
- name: Ter
type: ter
value: 81.0089
- name: ChrF
type: chrf
value: 87.4811
- name: CER
type: cer
value: 0.1041
- type: bleu
value: 8.7391
name: Bleu
- name: SubER
type: suber
value: 0.8189
pipeline_tag: automatic-speech-recognition
---
<!-- 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 Thai Lora - Magi Boss
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co./openai/whisper-small) on the Common Voice 11.0 dataset (Training Set 20000 row, Validation Set 500 row).
It achieves the following results on the evaluation set:
- Loss: 0.1894
- WER: 0.8101
- TER: 81.0089
- ChrF: 87.4811
- CER: 0.1041
- BLEU: 8.7391
- SubER: 0.8189
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 25
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Ter | Chrf | Cer | Bleu | SubER |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:-------:|:------:|:------:|:---------:|
| 0.3053 | 0.32 | 50 | 0.2052 | 0.8457 | 84.5697 | 86.6971 | 0.1115 | 7.8703 | 0.8640 |
| 0.3752 | 0.64 | 100 | 0.1937 | 0.8323 | 83.2344 | 86.9801 | 0.1087 | 8.1510 | 0.8469 |
| 0.2794 | 0.96 | 150 | 0.1894 | 0.8101 | 81.0089 | 87.4811 | 0.1041 | 8.7391 | 0.8189 |
### Framework versions
- PEFT 0.12.1.dev0
- Transformers 4.45.0.dev0
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1 |