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--- |
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library_name: transformers |
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base_model: csebuetnlp/banglabert |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: results |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# results |
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This model is a fine-tuned version of [csebuetnlp/banglabert](https://huggingface.co/csebuetnlp/banglabert) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6504 |
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- Accuracy: 0.8201 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 3 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:--------:| |
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| 0.2063 | 0.2015 | 250 | 0.7486 | 0.7993 | |
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| 0.4038 | 0.4029 | 500 | 0.3953 | 0.8140 | |
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| 0.4264 | 0.6044 | 750 | 0.3772 | 0.8156 | |
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| 0.3938 | 0.8058 | 1000 | 0.3900 | 0.8146 | |
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| 0.393 | 1.0073 | 1250 | 0.4148 | 0.8172 | |
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| 0.2627 | 1.2087 | 1500 | 0.4601 | 0.8247 | |
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| 0.2864 | 1.4102 | 1750 | 0.4548 | 0.8185 | |
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| 0.2559 | 1.6116 | 2000 | 0.4390 | 0.8138 | |
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| 0.2607 | 1.8131 | 2250 | 0.4408 | 0.8215 | |
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| 0.247 | 2.0145 | 2500 | 0.4906 | 0.8241 | |
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| 0.1356 | 2.2160 | 2750 | 0.6311 | 0.8177 | |
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| 0.1462 | 2.4174 | 3000 | 0.6750 | 0.8150 | |
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| 0.1252 | 2.6189 | 3250 | 0.6950 | 0.8207 | |
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| 0.1339 | 2.8203 | 3500 | 0.6504 | 0.8201 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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