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---
library_name: transformers
language:
- ne
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- kiranpantha/OpenSLR54-Balanced-Nepali
metrics:
- wer
model-index:
- name: Whisper Tiny 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: 53.726851851851855
---
<!-- 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 Tiny Nepali - Kiran Pantha
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co./openai/whisper-tiny) on the OpenSLR54 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2933
- Wer: 53.7269
- Cer: 16.1186
## 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 |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|
| 0.8115 | 0.3597 | 300 | 0.7467 | 92.9167 | 34.9897 |
| 0.4976 | 0.7194 | 600 | 0.4963 | 79.2130 | 26.2625 |
| 0.3874 | 1.0791 | 900 | 0.4198 | 71.5046 | 22.6696 |
| 0.3422 | 1.4388 | 1200 | 0.3797 | 67.5926 | 20.8896 |
| 0.3179 | 1.7986 | 1500 | 0.3467 | 63.9120 | 19.3959 |
| 0.2451 | 2.1583 | 1800 | 0.3299 | 62.1528 | 18.6950 |
| 0.2167 | 2.5180 | 2100 | 0.3224 | 60.6713 | 18.3977 |
| 0.2428 | 2.8777 | 2400 | 0.3085 | 59.6528 | 17.6196 |
| 0.1862 | 3.2374 | 2700 | 0.3057 | 57.6620 | 16.9113 |
| 0.1795 | 3.5971 | 3000 | 0.3007 | 57.5231 | 16.7792 |
| 0.1758 | 3.9568 | 3300 | 0.2935 | 55.8565 | 16.5297 |
| 0.1496 | 4.3165 | 3600 | 0.2960 | 55.8796 | 16.3792 |
| 0.156 | 4.6763 | 3900 | 0.2940 | 55.4398 | 16.4819 |
| 0.1235 | 5.0360 | 4200 | 0.2915 | 54.4444 | 16.0085 |
| 0.1311 | 5.3957 | 4500 | 0.2936 | 54.4676 | 16.2801 |
| 0.1136 | 5.7554 | 4800 | 0.2933 | 53.7269 | 16.1186 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cxx11.abi
- Datasets 3.2.0
- Tokenizers 0.20.3
|