File size: 2,475 Bytes
12fee03 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 | ---
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: ner-classification
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# ner-classification
This model is a fine-tuned version of [BAAI/bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1650
- Precision: 0.9019
- Recall: 0.9266
- F1: 0.9141
- Accuracy: 0.9818
## 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_FUSED 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.9605 | 1.0 | 625 | 0.3528 | 0.7730 | 0.8223 | 0.7969 | 0.9629 |
| 0.3424 | 2.0 | 1250 | 0.2244 | 0.8615 | 0.8933 | 0.8771 | 0.9763 |
| 0.2283 | 3.0 | 1875 | 0.1831 | 0.8656 | 0.9093 | 0.8869 | 0.9785 |
| 0.1363 | 4.0 | 2500 | 0.1691 | 0.8847 | 0.9172 | 0.9007 | 0.9806 |
| 0.1088 | 5.0 | 3125 | 0.1673 | 0.8939 | 0.9212 | 0.9073 | 0.9810 |
| 0.0874 | 6.0 | 3750 | 0.1587 | 0.8909 | 0.9222 | 0.9063 | 0.9814 |
| 0.0816 | 7.0 | 4375 | 0.1624 | 0.8948 | 0.9246 | 0.9095 | 0.9814 |
| 0.0642 | 8.0 | 5000 | 0.1657 | 0.9002 | 0.9241 | 0.9120 | 0.9817 |
| 0.0586 | 9.0 | 5625 | 0.1653 | 0.9006 | 0.9254 | 0.9128 | 0.9818 |
| 0.0574 | 10.0 | 6250 | 0.1650 | 0.9019 | 0.9266 | 0.9141 | 0.9818 |
### Framework versions
- Transformers 5.16.1
- Pytorch 2.11.0+cu128
- Datasets 4.8.5
- Tokenizers 0.23.1
|