---
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: 0.2604166666666667
---

<!-- 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: 0.2182
- Wer: 0.2604

## 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 4.4889        | 0.1800 | 300  | 0.8423          | 0.8076 |
| 0.7028        | 0.3599 | 600  | 0.6309          | 0.5951 |
| 0.5787        | 0.5399 | 900  | 0.5455          | 0.5167 |
| 0.476         | 0.7199 | 1200 | 0.4670          | 0.5109 |
| 0.4094        | 0.8998 | 1500 | 0.4415          | 0.4382 |
| 0.3345        | 1.0798 | 1800 | 0.3395          | 0.3951 |
| 0.2545        | 1.2597 | 2100 | 0.3266          | 0.3609 |
| 0.2444        | 1.4397 | 2400 | 0.2814          | 0.3204 |
| 0.2214        | 1.6197 | 2700 | 0.2593          | 0.2947 |
| 0.1846        | 1.7996 | 3000 | 0.2256          | 0.2685 |
| 0.1783        | 1.9796 | 3300 | 0.2182          | 0.2604 |


### Framework versions

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