---
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: urdu-tts-phonemes-finetuned-extended
  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. -->

# urdu-tts-phonemes-finetuned-extended

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8014

## 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: 6
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 48
- total_eval_batch_size: 4
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss |
|:-------------:|:-------:|:-----:|:---------------:|
| 4.6038        | 0.9149  | 500   | 0.9382          |
| 3.9723        | 1.8289  | 1000  | 0.8982          |
| 3.8796        | 2.7429  | 1500  | 0.8837          |
| 3.7655        | 3.6569  | 2000  | 0.8691          |
| 3.7279        | 4.5709  | 2500  | 0.8611          |
| 3.6874        | 5.4849  | 3000  | 0.8507          |
| 3.6253        | 6.3989  | 3500  | 0.8450          |
| 3.5747        | 7.3129  | 4000  | 0.8403          |
| 3.5732        | 8.2269  | 4500  | 0.8419          |
| 3.5595        | 9.1409  | 5000  | 0.8367          |
| 3.5520        | 10.0549 | 5500  | 0.8339          |
| 3.5297        | 10.9698 | 6000  | 0.8357          |
| 3.5303        | 11.8838 | 6500  | 0.8333          |
| 3.5060        | 12.7978 | 7000  | 0.8260          |
| 3.4967        | 13.7118 | 7500  | 0.8256          |
| 3.5028        | 14.6258 | 8000  | 0.8239          |
| 3.4786        | 15.5398 | 8500  | 0.8211          |
| 3.4918        | 16.4538 | 9000  | 0.8209          |
| 3.4901        | 17.3678 | 9500  | 0.8193          |
| 3.4815        | 18.2818 | 10000 | 0.8204          |
| 3.4688        | 19.1958 | 10500 | 0.8163          |
| 3.4426        | 20.1098 | 11000 | 0.8160          |
| 3.4519        | 21.0238 | 11500 | 0.8157          |
| 3.4514        | 21.9387 | 12000 | 0.8138          |
| 3.4341        | 22.8527 | 12500 | 0.8148          |
| 3.4341        | 23.7667 | 13000 | 0.8114          |
| 3.4261        | 24.6807 | 13500 | 0.8129          |
| 3.4276        | 25.5947 | 14000 | 0.8111          |
| 3.4234        | 26.5087 | 14500 | 0.8086          |
| 3.4379        | 27.4227 | 15000 | 0.8083          |
| 3.4171        | 28.3367 | 15500 | 0.8055          |
| 3.4083        | 29.2507 | 16000 | 0.8067          |
| 3.4227        | 30.1647 | 16500 | 0.8090          |
| 3.4050        | 31.0787 | 17000 | 0.8063          |
| 3.4144        | 31.9936 | 17500 | 0.8072          |
| 3.3968        | 32.9076 | 18000 | 0.8028          |
| 3.4001        | 33.8216 | 18500 | 0.8056          |
| 3.3873        | 34.7356 | 19000 | 0.8032          |
| 3.4032        | 35.6496 | 19500 | 0.8057          |
| 3.3936        | 36.5636 | 20000 | 0.8040          |
| 3.3829        | 37.4776 | 20500 | 0.8036          |
| 3.3927        | 38.3916 | 21000 | 0.8034          |
| 3.3895        | 39.3056 | 21500 | 0.8037          |
| 3.3789        | 40.2196 | 22000 | 0.8027          |
| 3.3938        | 41.1336 | 22500 | 0.8020          |
| 3.3907        | 42.0476 | 23000 | 0.8018          |
| 3.3752        | 42.9625 | 23500 | 0.8004          |
| 3.3759        | 43.8765 | 24000 | 0.8009          |
| 3.3807        | 44.7905 | 24500 | 0.8015          |
| 3.3808        | 45.7045 | 25000 | 0.8030          |
| 3.3720        | 46.6185 | 25500 | 0.8016          |
| 3.3851        | 47.5325 | 26000 | 0.8018          |
| 3.3733        | 48.4465 | 26500 | 0.8007          |
| 3.3703        | 49.3605 | 27000 | 0.8014          |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.3
- Tokenizers 0.22.2