DL2_hw2
This model is a fine-tuned version of BAAI/bge-small-en-v1.5 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0998
- Precision: 0.8586
- Recall: 0.9015
- F1: 0.8795
- Accuracy: 0.9767
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: 8
- eval_batch_size: 8
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.2279 | 1.0 | 1250 | 0.1480 | 0.8033 | 0.8624 | 0.8318 | 0.9686 |
| 0.114 | 2.0 | 2500 | 0.1048 | 0.8545 | 0.8944 | 0.8740 | 0.9760 |
| 0.0817 | 3.0 | 3750 | 0.0998 | 0.8586 | 0.9015 | 0.8795 | 0.9767 |
Framework versions
- Transformers 4.57.0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
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Model tree for vsinitsynav/DL2_hw2
Base model
BAAI/bge-small-en-v1.5