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---
library_name: transformers
language:
- ne
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
datasets:
- kiranpantha/OpenSLR54-Whisper
metrics:
- wer
model-index:
- name: Whisper Large v3 Turbo Nepali - Kiran Pantha
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: OpenSLR54
type: kiranpantha/OpenSLR54-Whisper
config: default
split: test
args: 'config: ne, split: test'
metrics:
- name: Wer
type: wer
value: 23.63425925925926
---
<!-- 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-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the OpenSLR54 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1707
- Wer: 23.6343
- Cer: 5.4903
## 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: Use 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 | Validation Loss | Wer | Cer |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|
| 0.3073 | 0.3597 | 300 | 0.2895 | 53.2870 | 13.5643 |
| 0.2457 | 0.7194 | 600 | 0.2396 | 45.3704 | 11.6816 |
| 0.166 | 1.0791 | 900 | 0.2062 | 37.9167 | 9.6668 |
| 0.1477 | 1.4388 | 1200 | 0.1949 | 37.4306 | 9.3071 |
| 0.1284 | 1.7986 | 1500 | 0.1680 | 32.6620 | 8.3235 |
| 0.0745 | 2.1583 | 1800 | 0.1706 | 31.1574 | 7.5272 |
| 0.0701 | 2.5180 | 2100 | 0.1661 | 32.0370 | 7.7217 |
| 0.0777 | 2.8777 | 2400 | 0.1599 | 28.6111 | 7.1308 |
| 0.0455 | 3.2374 | 2700 | 0.1723 | 28.7037 | 7.0097 |
| 0.0375 | 3.5971 | 3000 | 0.1579 | 26.9444 | 6.3674 |
| 0.0374 | 3.9568 | 3300 | 0.1639 | 26.8981 | 6.2794 |
| 0.0171 | 4.3165 | 3600 | 0.1711 | 25.3241 | 6.2280 |
| 0.0219 | 4.6763 | 3900 | 0.1638 | 25.0 | 5.9307 |
| 0.0089 | 5.0360 | 4200 | 0.1635 | 24.5139 | 5.7435 |
| 0.0072 | 5.3957 | 4500 | 0.1717 | 24.1898 | 5.5711 |
| 0.0059 | 5.7554 | 4800 | 0.1707 | 23.6343 | 5.4903 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cxx11.abi
- Datasets 3.2.0
- Tokenizers 0.20.3
|