---
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