metadata
license: mit
base_model: UmarRamzan/w2v2-bert-urdu
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v2-bert-urdu
results: []
language:
- ur
w2v2-bert-urdu
This model is a fine-tuned version of 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