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---
library_name: transformers
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v-bert-punjabi
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. -->
# w2v-bert-punjabi
This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1810
- Wer: 0.1029
## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use adamw_torch 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
- training_steps: 30000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 0.4419 | 0.2174 | 2000 | 0.3828 | 0.2268 |
| 0.3492 | 0.4348 | 4000 | 0.3401 | 0.1836 |
| 0.3205 | 0.6522 | 6000 | 0.2932 | 0.1712 |
| 0.2813 | 0.8696 | 8000 | 0.2844 | 0.1590 |
| 0.255 | 1.0870 | 10000 | 0.2562 | 0.1469 |
| 0.2451 | 1.3043 | 12000 | 0.2431 | 0.1386 |
| 0.2305 | 1.5217 | 14000 | 0.2299 | 0.1312 |
| 0.2156 | 1.7391 | 16000 | 0.2191 | 0.1274 |
| 0.2119 | 1.9565 | 18000 | 0.2269 | 0.1205 |
| 0.182 | 2.1739 | 20000 | 0.2091 | 0.1181 |
| 0.1789 | 2.3913 | 22000 | 0.1980 | 0.1136 |
| 0.1766 | 2.6087 | 24000 | 0.1945 | 0.1092 |
| 0.1657 | 2.8261 | 26000 | 0.1881 | 0.1079 |
| 0.1461 | 3.0435 | 28000 | 0.1809 | 0.1050 |
| 0.1454 | 3.2609 | 30000 | 0.1810 | 0.1029 |
### Framework versions
- Transformers 4.48.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
|