metadata
library_name: transformers
license: mit
base_model: BAAI/bge-small-en-v1.5
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: dl2_ner_hw2
results: []
dl2_ner_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: 0.0814
- Precision: 0.8982
- Recall: 0.9239
- F1: 0.9109
- Accuracy: 0.9814
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: 16
- seed: 42
- 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
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.4629 | 1.0 | 625 | 0.1731 | 0.7698 | 0.8211 | 0.7946 | 0.9629 |
| 0.1715 | 2.0 | 1250 | 0.1127 | 0.8544 | 0.8921 | 0.8729 | 0.9757 |
| 0.1158 | 3.0 | 1875 | 0.0934 | 0.8609 | 0.9093 | 0.8844 | 0.9774 |
| 0.0687 | 4.0 | 2500 | 0.0858 | 0.8854 | 0.9150 | 0.8999 | 0.9803 |
| 0.0559 | 5.0 | 3125 | 0.0845 | 0.8817 | 0.9185 | 0.8998 | 0.9790 |
| 0.0454 | 6.0 | 3750 | 0.0811 | 0.8853 | 0.9196 | 0.9021 | 0.9798 |
| 0.0432 | 7.0 | 4375 | 0.0816 | 0.8876 | 0.9226 | 0.9048 | 0.9802 |
| 0.0336 | 8.0 | 5000 | 0.0815 | 0.8983 | 0.9231 | 0.9105 | 0.9813 |
| 0.0304 | 9.0 | 5625 | 0.0816 | 0.9005 | 0.9241 | 0.9121 | 0.9815 |
| 0.0296 | 10.0 | 6250 | 0.0814 | 0.8982 | 0.9239 | 0.9109 | 0.9814 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.11.0+cu128
- Datasets 3.4.1
- Tokenizers 0.21.4