metadata
library_name: transformers
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v-bert-bengali-model
results: []
w2v-bert-bengali-model
This model is a fine-tuned version of facebook/w2v-bert-2.0 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1759
- Wer: 0.1737
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 OptimizerNames.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
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4772 | 0.4336 | 2000 | 0.3677 | 0.3733 |
| 0.3599 | 0.8671 | 4000 | 0.3126 | 0.3000 |
| 0.2908 | 1.3007 | 6000 | 0.2661 | 0.2659 |
| 0.2594 | 1.7342 | 8000 | 0.2433 | 0.2441 |
| 0.2041 | 2.1678 | 10000 | 0.2290 | 0.2279 |
| 0.1933 | 2.6013 | 12000 | 0.2107 | 0.2146 |
| 0.1676 | 3.0349 | 14000 | 0.2096 | 0.2117 |
| 0.1463 | 3.4685 | 16000 | 0.1956 | 0.1981 |
| 0.1332 | 3.9020 | 18000 | 0.1772 | 0.1848 |
| 0.106 | 4.3356 | 20000 | 0.1816 | 0.1788 |
| 0.1014 | 4.7691 | 22000 | 0.1759 | 0.1737 |
Framework versions
- Transformers 4.53.0
- Pytorch 2.7.0+cu126
- Datasets 2.18.0
- Tokenizers 0.21.1