sambodhan_department_classifier
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0000
- Accuracy: 1.0
- F1 Macro: 1.0
- F1 Weighted: 1.0
- Precision Macro: 1.0
- Recall Macro: 1.0
- Precision Weighted: 1.0
- Recall Weighted: 1.0
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_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted | Precision Macro | Recall Macro | Precision Weighted | Recall Weighted |
|---|---|---|---|---|---|---|---|---|---|---|
| 0.1543 | 0.4098 | 50 | 0.0277 | 0.9300 | 0.9301 | 0.9304 | 0.9327 | 0.9298 | 0.9331 | 0.9300 |
| 0.0159 | 0.8197 | 100 | 0.0015 | 0.9877 | 0.9876 | 0.9876 | 0.9881 | 0.9877 | 0.9882 | 0.9877 |
| 0.0013 | 1.2295 | 150 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0003 | 1.6393 | 200 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.9.0+cu128
- Datasets 4.3.0
- Tokenizers 0.22.1
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Model tree for sambodhan/sambodhan_department_classifier
Base model
FacebookAI/xlm-roberta-base