---
base_model: BAAI/bge-m3-retromae
tags:
- generated_from_trainer
datasets:
- adalbertojunior/segmentacao
model-index:
- name: test_crf
  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. -->

# test_crf

This model is a fine-tuned version of [BAAI/bge-m3-retromae](https://huggingface.co/BAAI/bge-m3-retromae) on the adalbertojunior/segmentacao dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.0063
- eval_model_preparation_time: 0.0032
- eval_precision: 0.6294
- eval_recall: 0.6832
- eval_f1: 0.6552
- eval_accuracy: 0.9989
- eval_runtime: 12.8447
- eval_samples_per_second: 3.893
- eval_steps_per_second: 3.893
- step: 0

## Usage

```python
from transformers import pipeline
segmenter = pipeline("ner", model="./models/test_crf_v2", aggregation_strategy="simple", device=0)
entities = segmenter(text)
```
## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0

### Framework versions

- Transformers 4.43.4
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1