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---
library_name: transformers
language:
- ne
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
datasets:
- kiranpantha/OpenSLR54-Balanced-Nepali
metrics:
- wer
model-index:
- name: Whisper Large v3 Nepali - Kiran Pantha
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: OpenSLR54
type: kiranpantha/OpenSLR54-Balanced-Nepali
config: default
split: test
args: 'config: ne, split: test'
metrics:
- name: Wer
type: wer
value: 18.72503840245776
---
<!-- 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 Turbo Nepali - Kiran Pantha
This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the OpenSLR54 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0876
- Wer: 18.7250
- Cer: 4.4861
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Cer | Validation Loss | Wer |
|:-------------:|:------:|:----:|:-------:|:---------------:|:-------:|
| 0.2266 | 0.1200 | 300 | 11.9034 | 0.2345 | 44.7619 |
| 0.208 | 0.2399 | 600 | 11.3157 | 0.2132 | 41.1060 |
| 0.185 | 0.3599 | 900 | 9.4204 | 0.1753 | 35.6068 |
| 0.1567 | 0.4798 | 1200 | 8.8596 | 0.1634 | 33.9324 |
| 0.1411 | 0.5998 | 1500 | 8.7004 | 0.1523 | 33.0568 |
| 0.1377 | 0.7197 | 1800 | 7.3120 | 0.1371 | 29.7849 |
| 0.1147 | 0.8397 | 2100 | 7.0010 | 0.1332 | 27.7112 |
| 0.1116 | 0.9596 | 2400 | 6.5798 | 0.1212 | 26.3287 |
| 0.0757 | 1.0796 | 2700 | 6.1268 | 0.1193 | 24.7773 |
| 0.0609 | 1.1995 | 3000 | 5.8991 | 0.1154 | 24.6237 |
| 0.0612 | 1.3195 | 3300 | 5.2599 | 0.1091 | 22.0737 |
| 0.0627 | 1.4394 | 3600 | 5.3579 | 0.1045 | 21.6283 |
| 0.0582 | 1.5594 | 3900 | 5.1938 | 0.0995 | 21.5054 |
| 0.0551 | 1.6793 | 4200 | 4.7947 | 0.0956 | 19.8771 |
| 0.052 | 1.7993 | 4500 | 4.5473 | 0.0897 | 19.1244 |
| 0.0438 | 1.9192 | 4800 | 4.4861 | 0.0876 | 18.7250 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cxx11.abi
- Datasets 3.2.0
- Tokenizers 0.21.0
|