metadata
library_name: transformers
base_model: csebuetnlp/banglabert
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: repo_name
results: []
repo_name
This model is a fine-tuned version of csebuetnlp/banglabert on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4297
- Accuracy: 0.8705
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- 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: cosine
- lr_scheduler_warmup_steps: 645
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3313 | 0.4735 | 1000 | 0.3475 | 0.8446 |
| 0.3384 | 0.9470 | 2000 | 0.3331 | 0.8630 |
| 0.2469 | 1.4205 | 3000 | 0.3431 | 0.8615 |
| 0.2392 | 1.8939 | 4000 | 0.3347 | 0.8705 |
| 0.1737 | 2.3674 | 5000 | 0.4186 | 0.8659 |
| 0.1481 | 2.8409 | 6000 | 0.4297 | 0.8705 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1