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---
license: mit
base_model: UmarRamzan/w2v2-bert-urdu
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 [UmarRamzan/w2v2-bert-urdu](https://huggingface.co/UmarRamzan/w2v2-bert-urdu) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3681
- Wer: 0.2929
## 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: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.4362 | 0.1695 | 50 | 0.4144 | 0.3213 |
| 0.3776 | 0.3390 | 100 | 0.4029 | 0.3137 |
| 0.3918 | 0.5085 | 150 | 0.4095 | 0.3060 |
| 0.3968 | 0.6780 | 200 | 0.3961 | 0.3060 |
| 0.3685 | 0.8475 | 250 | 0.3681 | 0.2929 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
|