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---
library_name: transformers
language:
- ne
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
datasets:
- kiranpantha/OpenSLR54-Balanced-Nepali
metrics:
- wer
model-index:
- name: Wave2Vec2-Bert2.0 - 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: train,test'
metrics:
- name: Wer
type: wer
value: 1.0004629629629629
---
<!-- 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. -->
# Wave2Vec2-Bert2.0 - Kiran Pantha
This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the OpenSLR54 dataset.
It achieves the following results on the evaluation set:
- Loss: 10.8771
- Wer: 1.0005
- Cer: 0.9690
## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.SGD and the args are:
No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 2
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|
| 16.7814 | 0.1800 | 300 | 16.3800 | 1.0007 | 3.1059 |
| 16.2838 | 0.3599 | 600 | 15.8109 | 1.0005 | 2.9213 |
| 15.5569 | 0.5399 | 900 | 15.0093 | 1.0005 | 2.5754 |
| 15.0336 | 0.7199 | 1200 | 14.1309 | 1.0002 | 2.0061 |
| 13.9247 | 0.8998 | 1500 | 13.2986 | 1.0002 | 1.5023 |
| 13.1967 | 1.0798 | 1800 | 12.5663 | 1.0002 | 1.2076 |
| 12.4844 | 1.2597 | 2100 | 11.9662 | 1.0002 | 1.0769 |
| 11.8394 | 1.4397 | 2400 | 11.4978 | 1.0005 | 1.0134 |
| 11.4607 | 1.6197 | 2700 | 11.1599 | 1.0005 | 0.9855 |
| 11.2266 | 1.7996 | 3000 | 10.9534 | 1.0005 | 0.9733 |
| 11.0877 | 1.9796 | 3300 | 10.8771 | 1.0005 | 0.9690 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cxx11.abi
- Datasets 3.2.0
- Tokenizers 0.21.0
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