---
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v2-bert-urdu
  results: []
---

<!-- 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. -->

# w2v2-bert-urdu

This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6237
- Wer: 0.4732

## 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-06
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 7.3111        | 0.1695 | 50   | 4.0973          | 1.0    |
| 3.6426        | 0.3390 | 100  | 3.0408          | 1.0    |
| 2.7471        | 0.5085 | 150  | 2.0725          | 0.9836 |
| 1.4561        | 0.6780 | 200  | 0.9029          | 0.5519 |
| 0.85          | 0.8475 | 250  | 0.6233          | 0.4219 |
| 0.6703        | 1.0169 | 300  | 0.5772          | 0.4590 |
| 0.6025        | 1.1864 | 350  | 0.5479          | 0.4077 |
| 0.633         | 1.3559 | 400  | 0.6068          | 0.4798 |
| 0.6775        | 1.5254 | 450  | 0.6257          | 0.4787 |
| 0.7196        | 1.6949 | 500  | 0.6241          | 0.4765 |
| 0.6955        | 1.8644 | 550  | 0.6237          | 0.4732 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1