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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: 0.44317605276509386
---
<!-- 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: 0.4271
- Wer: 0.4432
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.8954 | 0.15 | 300 | 1.0556 | 0.8694 |
| 0.938 | 0.3 | 600 | 0.8641 | 0.7710 |
| 0.8269 | 0.45 | 900 | 0.6742 | 0.6457 |
| 0.729 | 0.6 | 1200 | 0.6141 | 0.5665 |
| 0.6879 | 0.75 | 1500 | 0.6085 | 0.5791 |
| 0.6386 | 0.9 | 1800 | 0.5424 | 0.5333 |
| 0.5923 | 1.05 | 2100 | 0.4991 | 0.4880 |
| 0.5403 | 1.2 | 2400 | 0.4821 | 0.4870 |
| 0.4965 | 1.35 | 2700 | 0.4794 | 0.4793 |
| 0.5249 | 1.5 | 3000 | 0.4520 | 0.4607 |
| 0.4936 | 1.65 | 3300 | 0.4569 | 0.4586 |
| 0.473 | 1.8 | 3600 | 0.4527 | 0.4606 |
| 0.4414 | 1.95 | 3900 | 0.4271 | 0.4432 |
### Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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