bert-tiny-llm-router
This model is a fine-tuned version of prajjwal1/bert-tiny on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4112
- F1: 0.9003
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: 16
- total_train_batch_size: 32
- 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_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.6131 | 1.0 | 479 | 0.6153 | 0.5854 |
| 0.5293 | 2.0 | 958 | 0.5049 | 0.8647 |
| 0.4771 | 3.0 | 1437 | 0.4485 | 0.8902 |
| 0.4546 | 4.0 | 1916 | 0.4198 | 0.8980 |
| 0.4545 | 5.0 | 2395 | 0.4112 | 0.9003 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.7.1
- Datasets 3.6.0
- Tokenizers 0.21.1
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Base model
prajjwal1/bert-tiny