---
library_name: transformers
language:
- ne
license: mit
base_model: kiranpantha/w2v-bert-2.0-nepali-iteration-test
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: 0.4636116306750553
---

<!-- 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 [kiranpantha/w2v-bert-2.0-nepali-iteration-test](https://huggingface.co/kiranpantha/w2v-bert-2.0-nepali-iteration-test) on the OpenSLR54 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4545
- Wer: 0.4636

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.392         | 0.15  | 300  | 0.4561          | 0.4579 |
| 0.5077        | 0.3   | 600  | 0.5402          | 0.5145 |
| 0.5371        | 0.45  | 900  | 0.5083          | 0.4923 |
| 0.4943        | 0.6   | 1200 | 0.5103          | 0.5147 |
| 0.5049        | 0.75  | 1500 | 0.4811          | 0.4752 |
| 0.4809        | 0.9   | 1800 | 0.4751          | 0.4689 |
| 0.4633        | 1.05  | 2100 | 0.5031          | 0.4883 |
| 0.3843        | 1.2   | 2400 | 0.4703          | 0.4573 |
| 0.3753        | 1.35  | 2700 | 0.4542          | 0.4497 |
| 0.356         | 1.5   | 3000 | 0.4510          | 0.4503 |
| 0.3668        | 1.65  | 3300 | 0.4591          | 0.4524 |
| 0.3386        | 1.8   | 3600 | 0.4399          | 0.4459 |
| 0.3452        | 1.95  | 3900 | 0.4545          | 0.4636 |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1