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library_name: transformers
base_model: csebuetnlp/banglabert
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
- precision
- recall
model-index:
- name: basic_transformer
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. -->
# basic_transformer
This model is a fine-tuned version of [csebuetnlp/banglabert](https://huggingface.co/csebuetnlp/banglabert) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0173
- F1: 0.9970
- Accuracy: 0.997
- Precision: 0.9970
- Recall: 0.997
## 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: 32
- 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: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:|:------:|
| No log | 1.0 | 438 | 0.0235 | 0.9970 | 0.997 | 0.9970 | 0.997 |
| 0.0328 | 2.0 | 876 | 0.0182 | 0.996 | 0.996 | 0.996 | 0.996 |
| 0.0191 | 3.0 | 1314 | 0.0173 | 0.9970 | 0.997 | 0.9970 | 0.997 |
### Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2
|