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: 0.3833
- F1: 0.8960
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 |
|---|---|---|---|---|
| 0.5698 | 1.0 | 479 | 0.5538 | 0.8566 |
| 0.4957 | 2.0 | 958 | 0.4610 | 0.8923 |
| 0.4514 | 3.0 | 1437 | 0.4140 | 0.8953 |
| 0.4329 | 4.0 | 1916 | 0.3903 | 0.8958 |
| 0.4358 | 4.9910 | 2390 | 0.3833 | 0.8960 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.7.0
- Datasets 3.1.0
- Tokenizers 0.21.1
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Model tree for m-misiura-rh/bert-tiny-llm-router
Base model
prajjwal1/bert-tiny