---
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-without
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/elizkaveta/ner-bge-small/runs/3pjvf28t)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/elizkaveta/ner-with/runs/4ozy99g6)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/elizkaveta/ner-without/runs/pf35qjqr)
# ner-without

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: 0.0829
- Precision: 0.9106
- Recall: 0.9291
- F1: 0.9198
- Accuracy: 0.9826

## 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: 5.6524599759245336e-05
- train_batch_size: 8
- eval_batch_size: 32
- 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
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1031        | 1.0   | 1250 | 0.1021          | 0.8331    | 0.9021 | 0.8662 | 0.9735   |
| 0.0664        | 2.0   | 2500 | 0.0878          | 0.8905    | 0.9130 | 0.9016 | 0.9795   |
| 0.0442        | 3.0   | 3750 | 0.0817          | 0.9017    | 0.9221 | 0.9118 | 0.9813   |
| 0.0287        | 4.0   | 5000 | 0.0859          | 0.9106    | 0.9256 | 0.9180 | 0.9823   |
| 0.0117        | 5.0   | 6250 | 0.0829          | 0.9106    | 0.9291 | 0.9198 | 0.9826   |


### Framework versions

- Transformers 4.53.3
- Pytorch 2.6.0+cu124
- Datasets 4.1.1
- Tokenizers 0.21.2